@article {13511, title = {Pre-Analytical Variables Influencing Stability of Blood-Based Biomarkers of Neuropathology.}, journal = {Journal of Alzheimer{\textquoteright}s Disease}, year = {Forthcoming}, abstract = {

BACKGROUND: Sample collection and preanalytical protocols may significantly impact the results of large-scale epidemiological studies incorporating blood-based biomarkers of neuropathology.

OBJECTIVE: To evaluate the stability and assay variability of several blood-based biomarkers of neuropathology for common preanalytical conditions.

METHODS: We collected serum and plasma samples from 41 participants and evaluated the effect of processing delay of up to 72 h when stored at 4oC, three freeze-thaw cycles, and a combination of 48-h processing delay when stored at 4oC and three freeze-thaw cycles on biomarker stability. Using the Simoa assay (Quanterix Inc.), we measured amyloid-β 40 (Aβ40), amyloid-β 42 (Aβ42), neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and phosphorylated tau 181 (p-tau-181).

RESULTS: We found that Aβ40 and Aβ42 levels significantly decreased after a 24-h processing delay in both plasma and serum samples, and a single freeze-thaw cycle (p < 0.0001). Nevertheless, serum Aβ42/40 ratio remained stable with a processing delay up to 48 h while plasma Aβ42/40 ratio showed only small but significant increase with a delay up to 72 h. Both plasma and serum GFAP and NfL levels were only modestly affected by processing delay and freeze-thaw cycles. Plasma p-tau-181 levels notably increased with a 24-, 48-, and 72-h processing delay, but remained stable in serum. Intra-individual variation over two weeks was minimal for all biomarkers and their levels were substantially lower in serum when compared with plasma.

CONCLUSION: These results suggest that standardizing preanalytical variables will allow robust measurements of biomarkers of neuropathology in population studies.

}, keywords = {Alzheimer, amyloid-β, blood-based biomarkers, pre-analytical variables, Simoa assay, stability}, issn = {1875-8908}, doi = {10.3233/JAD-230384}, author = {Panikkar, Daniel and Vivek, Sithara and Crimmins, Eileen and Jessica Faul and Kenneth M. Langa and Bharat Thyagarajan} } @article {13311, title = {Age-related differences in T cell subsets and markers of subclinical inflammation in aging are independently associated with type 2 diabetes in the Health and Retirement Study.}, journal = {Canadian Journal of Diabetes}, volume = {47}, year = {2023}, pages = {594-602.e6}, abstract = {

AIMS: Age-related changes in adaptive immunity and subclinical inflammation are both important risk factors for diabetes in older adults. We evaluated the independent association between T cell subsets, subclinical inflammation, and diabetes risk in the Health and Retirement Study (HRS).

METHODS: We measured 11 T cell subsets, five pro-inflammatory markers, and two anti-inflammatory markers from the 2016 wave of HRS (baseline). Diabetes/prediabetes status was estimated at the 2016, 2018, and 2020 waves of HRS based on levels of blood glucose/HbA1C in plasma or self-reported status. We used survey generalized logit models to evaluate the cross-sectional associations and Cox proportional hazard models to evaluate longitudinal associations.

RESULTS: Among 8540 participants (age 56-107), 27.6\% had prevalent type 2 diabetes and 31.1\% had prediabetes in the 2016 survey. After adjusting for age, sex, race/ethnicity, education, obesity, smoking, comorbidity index and cytomegalovirus (CMV) seropositivity, individuals with type 2 diabetes had lower na{\"\i}ve T cells and higher memory and terminal effector T cells as compared to normoglycemic individuals. Among 3230 normoglycemic participants at the 2016 survey, the incidence of diabetes was 1.8\% over four years of follow up. The baseline percentage of CD4+ effector memory T cells was associated with a lower risk of incident diabetes (HR=0.63; 95\% CI [0.49, 0.80], p=0.0003) after adjustment for covariates. Baseline levels of Interleukin-6 (IL-6) was associated with risk of incident diabetes (HR=1.52; 95\% CI [1.18, 1.97], p=0.002). The associations between age-related changes in CD4+ effector memory T cells and risk of incident diabetes remained unchanged after adjustment for subclinical inflammation, though adjusting for CD4+ effector memory T cells nullified the association between IL-6 and incident diabetes.

CONCLUSIONS: This study showed that the baseline percentage of CD4+ effector memory T cells was inversely associated with incident diabetes independent of subclinical inflammation, though CD4+ effector memory T cell subsets affected the relationship between IL-6 and incident diabetes. Further studies are needed to confirm and investigate mechanisms by which T cell immunity affects diabetes risk.

}, keywords = {age-related immune phenotype, CMV Seropositivity, Inflammation, memory T cells}, issn = {2352-3840}, doi = {10.1016/j.jcjd.2023.05.010}, author = {Vivek, Sithara and Crimmins, Eileen M and Prizment, Anna E and Meier, Helen C S and Ramasubramanian, Ramya and Barcelo, Helene and Jessica Faul and Bharat Thyagarajan} } @article {13510, title = {Cohabitation as a determinant of adaptive and innate immune cell profiles: Findings from the Health and Retirement Study.}, journal = {Brain, Behavior, and Immunity - Health}, volume = {33}, year = {2023}, pages = {100676}, abstract = {

INTRODUCTION: Non-genetic factors are important but poorly understood determinants of immune profiles. Age and Cytomegalovirus (CMV) infection remain two well documented non-genetic determinants of the immune profile. Recently, one study identified cohabitation in the same household as an important determinant of immune profiles.

METHODS: We used immunophenotyping data from the Health and Retirement Study (HRS) to evaluate the association between cohabitation and the adaptive (subsets of T-cells, B-cells) and innate immune profiles (subsets of monocytes, natural killer cells and neutrophils). We compared adaptive and innate immune cell profiles using immunophenotyping data from 1184 same-household pairs (cohabitating partners) to 1184 non-household pairs to evaluate the association between cohabitation and adaptive immune cell profiles. We used data from 1737 same-household pairs and 1737 non-household pairs to evaluate the association between cohabitation and innate cell profiles. Household and non-household pairs were matched on age ({\textpm}2years), educational background and race/ethnicity to minimize confounding due to these factors. The adaptive immune cells and innate immune cell profiles were compressed to two coordinates using multidimensional scaling (MDS). The Euclidean distances between same-household pairs were compared to the distances between non-household pairs for the adaptive and innate cell profiles separately using two sample independent t-tests. We also performed additional adjustment for age and BMI differences, CMV serostatus and smoking concordance/discordance status among household members.

RESULTS: For adaptive immune cell profiles, the mean Euclidean distance between same-household pairs was 4\% lower than the non-household pairs (p~=~0.03). When stratified by concordance for CMV serostatus among household pairs, the Euclidean distance was significantly lower by 8\% in the same-household pairs as compared to non-household pairs among those who were discordant for CMV serostatus (p~=~0.01) and among same-household pairs who were CMV seronegative (p~=~0.02) after covariate adjustment. The mean Euclidian distance between same-household pairs was also 8\% lower than non-household pairs for the innate immune cell profiles (p-value <0.0001) and this difference remained consistent across all strata of CMV infection.

DISCUSSION: This study confirms that cohabitation is associated with similarity in immune cell profiles. The differential effects of cohabitation on the adaptive and innate immune profiles suggest that further studies into the common environmental factors that influence individual immune cell subsets need to be evaluated in greater detail.

}, keywords = {cohabition, Immune System}, issn = {2666-3546}, doi = {10.1016/j.bbih.2023.100676}, author = {Ramasubramanian, Ramya and Kim, Jae Won and Guan, Weihua and Meier, Helen C S and Crimmins, Eileen and Jessica Faul and Bharat Thyagarajan} } @article {12923, title = {Epigenetic-based age acceleration in a representative sample of older Americans: Associations with aging-related morbidity and mortality.}, journal = {PNAS}, volume = {120}, year = {2023}, pages = {e2215840120}, abstract = {

Biomarkers developed from DNA methylation (DNAm) data are of growing interest as predictors of health outcomes and mortality in older populations. However, it is unknown how epigenetic aging fits within the context of known socioeconomic and behavioral associations with aging-related health outcomes in a large, population-based, and diverse sample. This study uses data from a representative, panel study of US older adults to examine the relationship between DNAm-based age acceleration measures in the prediction of cross-sectional and longitudinal health outcomes and mortality. We examine whether recent improvements to these scores, using principal component (PC)-based measures designed to remove some of the technical noise and unreliability in measurement, improve the predictive capability of these measures. We also examine how well DNAm-based measures perform against well-known predictors of health outcomes such as demographics, SES, and health behaviors. In our sample, age acceleration calculated using "second and third generation clocks," PhenoAge, GrimAge, and DunedinPACE, is consistently a significant predictor of health outcomes including cross-sectional cognitive dysfunction, functional limitations and chronic conditions assessed 2 y after DNAm measurement, and 4-y mortality. PC-based epigenetic age acceleration measures do not significantly change the relationship of DNAm-based age acceleration measures to health outcomes or mortality compared to earlier versions of these measures. While the usefulness of DNAm-based age acceleration as a predictor of later life health outcomes is quite clear, other factors such as demographics, SES, mental health, and health behaviors remain equally, if not more robust, predictors of later life outcomes.

}, keywords = {Acceleration, Aging, Biomarkers, Cross-Sectional Studies, DNA Methylation, Epigenesis, genetic}, issn = {1091-6490}, doi = {10.1073/pnas.2215840120}, author = {Jessica Faul and Jung K Kim and Levine, Morgan E and Bharat Thyagarajan and David R Weir and Eileen M. Crimmins} } @article {13630, title = {Immune cells are associated with mortality: the Health and Retirement Study.}, journal = {Frontiers in immunology}, volume = {14}, year = {2023}, pages = {1280144}, abstract = {

INTRODUCTION: Age-related immunosenescence is characterized by changes in immune cell subsets and is associated with mortality. However, since immunosenescence is associated with other concurrent age-related changes such as inflammation and multi-organ dysfunction, it is unclear whether the association between age-related immunosenescence and mortality is independent of other concurrent age-related changes. To address these limitations, we evaluated the independent association between immune cell subsets and mortality after adjustment for age-related inflammation and biologic age.

METHODS: Data for this study was obtained from the 2016 interview of the Health and Retirement Study (N=6802). Cox proportional hazards regression models were used to estimate the association between 25 immune cell subsets (11 T-cell subsets, 4 B-cell subsets, 3 monocyte subsets, 3 natural killer cell subsets, 3 dendritic cell subsets, and neutrophils) and 4-year mortality adjusting for covariates such as the Klemera-Doubal algorithm biological age, chronological age, gender, race/ethnicity, BMI, smoking status, comorbidity index, CMV seropositivity, and inflammatory latent variable comprising C-reactive protein, and 4 cytokines (interleukin-10, interleukin-1 receptor antagonist, interleukin-6, and soluble tumor necrosis factor).

RESULTS: Four hundred and seventy-six participants died during the study period with an overall median follow up time of 2.5 years. After controlling for covariates and adjustment for sample-weights, total T cells [HR: 0.86, p=0.004], NK CD56LO cells [HR: 0.88, p=0.005], and neutrophils [HR: 1.22, p=0.004] were significantly associated with mortality.

CONCLUSIONS: These findings support the idea that an aging immune system is associated with short-term mortality independent of age-related inflammation or other age-related measures of physiological dysfunction. If replicated in other external cohorts, these findings could identify novel targets for both monitoring and intervention to reduce the age-related mortality.

}, keywords = {Aging, Humans, Immunosenescence, Inflammation, Retirement, T-Lymphocyte Subsets}, issn = {1664-3224}, doi = {10.3389/fimmu.2023.1280144}, author = {Seshadri, Gokul and Vivek, Sithara and Prizment, Anna and Crimmins, Eileen M and Klopack, Eric T and Jessica Faul and Guan, Weihua and Meier, Helen C S and Bharat Thyagarajan} } @article {11926, title = {Age-related differences in T cell subsets in a nationally representative sample of people over age 55: Findings from the Health and Retirement Study.}, journal = {The Journals of Gerontology, Series A }, volume = {77}, year = {2022}, pages = {927-933}, abstract = {

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 na{\"\i}ve (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.

}, keywords = {Aging, CMV Seropositivity}, issn = {1758-535X}, doi = {10.1093/gerona/glab300}, author = {Bharat Thyagarajan and Jessica Faul and Vivek, Sithara and Jung K Kim and Nikolich-{\v Z}ugich, Janko and David R Weir and Eileen M. Crimmins} } @article {11930, title = {Cross sectional association between cytomegalovirus seropositivity, inflammation and cognitive impairment in elderly cancer survivors.}, journal = {Cancer Causes \& Control}, volume = {33}, year = {2022}, pages = {81-90}, abstract = {

PURPOSE: The higher prevalence of cognitive impairment/ dementia among cancer survivors is likely multifactorial. Since both exposures to cytomegalovirus (CMV) and inflammation are common among elderly cancer survivors, we evaluated their contribution towards dementia.

METHODS: Data from 1387 cancer survivors and 7004 participants without cancer in the 2016 wave of the Health and Retirement Study (HRS) was used in this study. Two inflammatory biomarkers, C-reactive protein (CRP) and neutrophil-lymphocyte ratio (NLR), were used to create an inflammation score. We used survey logistic regression adjusted for survey design parameters.

RESULTS: CMV seropositivity was not associated with cognitive impairment among cancer survivors (p = 0.2). In addition, inflammation was associated with elevated odds of cognitive impairment (OR = 2.2, 95\% CI [1.2, 4.2]). Cancer survivors who were both CMV seropositive and had increased inflammation had the highest odds of cognitive impairment compared to those who were CMV seronegative and had low inflammation (OR = 3.8, 95\% CI [1.5, 9.4]). The stratified analysis among cancer survivors showed this association was seen only among cancer survivors in whom the cancer was diagnosed within three years of measurement of inflammation score and CMV serostatus (OR = 18.5; 95\% CI [6.1, 56.1]).

CONCLUSION: The CMV seropositivity and high inflammation was associated with higher cognitive impairment among cancer survivors. The stronger associations seen among cancer survivors diagnosed within the last three years suggest that strategies to reduce CMV activation and inflammation during or immediately after cancer treatment may be important in reducing the prevalence of cognitive impairment/ dementia among cancer survivors.

}, keywords = {Cancer survivor, CMV Seropositivity, Dementia, Inflammation}, issn = {1573-7225}, doi = {https://doi.org/10.1007/s10552-021-01504-3}, author = {Vivek, Sithara and Heather Hammond Nelson and Anna Prizment and Jessica Faul and Eileen M. Crimmins and Bharat Thyagarajan} } @article {12568, title = {Evaluation of T-cell aging-related immune phenotypes in the context of biological aging and multimorbidity in the Health and Retirement Study.}, journal = {Immunity \& Ageing}, volume = {19}, year = {2022}, pages = {33}, abstract = {

BACKGROUND: Cellular changes in adaptive immune system accompany the process of aging and contribute to an aging-related immune phenotype (ARIP) characterized by decrease in na{\"\i}ve T-cells (T) and increase in memory T-cells (T). A population-representative marker of ARIP and its associations with biological aging and age-related chronic conditions have not been studied previously.

METHODS: We developed two ARIP indicators based on well understood age-related changes in T cell distribution: T/(T (Central Memory) + T (Effector Memory) + T (Effector)) (referred as T/T) in CD4 + and CD8 + T-cells. We compared them with existing ARIP measures including CD4/CD8 ratio and CD8 + TN cells by evaluating associations with chronological age and the Klemera Doubal measure of biological age (measured in years) using linear regression, multimorbidity using multinomial logistic regression and two-year mortality using logistic regression.

RESULTS: CD8 + T and CD8 + T/T had the strongest inverse association with chronological age (beta estimates: -3.41 and -3.61 respectively; p-value < 0.0001) after adjustment for sex, race/ethnicity and CMV status. CD4 + T/T and CD4 + T~had the strongest inverse association with biological age (β = -0.23; p = 0.003 and β = -0.24; p = 0.004 respectively) after adjustment for age, sex, race/ethnicity and CMV serostatus. CD4/CD8 ratio was not associated with chronological age or biological age. CD4 + T/T and CD4 + T was inversely associated with multimorbidity. For CD4 + T/T, people with 2 chronic conditions had an odds ratio of for 0.74 (95\%CI: 0.63-0.86 p = 0.0003) compared to those without any chronic conditions while those with 3 chronic conditions had an odds ratio of 0.75 (95\% CI: 0.63-0.90; p = 0.003) after adjustment for age, sex, race/ethnicity, CMV serostatus, smoking, and BMI. The results for the CD4 + T subset were very similar to the associations seen with the CD4 + T/T. CD4 + T/T and CD4 + T were both associated with two-year mortality (OR = 0.80 (95\% CI: 0.67-0.95; p = 0.01) and 0.81 (0.70-0.94; p = 0.01), respectively).

CONCLUSION: CD4 + T/T and CD4 + T had a stronger association with biological age, age-related morbidity and mortality compared to other ARIP measures. Future longitudinal studies are needed to evaluate the utility of the CD4 + subsets in predicting the risk of aging-related outcomes.

}, keywords = {Adaptive immunity, biological aging, immune aging, multimorbidity}, issn = {1742-4933}, doi = {10.1186/s12979-022-00290-z}, author = {Ramasubramanian, Ramya and Meier, Helen C S and Vivek, Sithara and Klopack, Eric and Eileen M. Crimmins and Jessica Faul and Nikolich-{\v Z}ugich, Janko and Bharat Thyagarajan} } @article {12877, title = {The role of cohabitation on adaptive and innate immune cell profiles in the Health and Retirement Study}, journal = {American Journal of Clinical Pathology}, volume = {158}, year = {2022}, pages = {S2}, abstract = {Immune cells distribution is shaped by numerous factors including environmental factors, age, and genetics. Cohabitation has been associated with similar microbiomes, possibly due to dietary patterns and exposure to similar pathogens but has not been studied in the context of adaptive and innate immune systems previously. We used immunophenotyping data of 2283 households with participants living in the same household and compared it to 2283 randomly generated pairs of participants from the Health and Retirement study. The adaptive immune cells (subsets of T-cells and B-cells), and innate immune cells (monocytes, natural killer cells, and neutrophils) were compressed to two coordinates using multidimensional scaling. The Euclidean distances between participants in the same household were compared to the distances between the random pairs of participants using two sample independent t-tests. The mean distances of the immune coordinate points for adaptive immune cells between participants in the same household were lower than the randomly paired participants (p-value \< 0.0001) and the variability of intra-household distances was lower than the random pairs (IQR: 7.18 vs 8.99). For the innate immune cells, the mean distances between participants in the same household were slightly lower than the randomly paired participants (p-value = 0.03) but the variability of the intra-household distances was higher than the random pairs (IQR: 4.08 vs 3.65). Variability in the adaptive immune system among participants living in the same household were substantially lower indicating the influence of shared environmental conditions in determining the adaptive immune profiles.}, keywords = {adaptive immune cells, Cohabitation, Households}, doi = {10.1093/ajcp/aqac126.002}, author = {Ramasubramanian, Ramya and Meier, Helen and Eileen M. Crimmins and Jessica Faul and Bharat Thyagarajan} } @article {13514, title = {Socioeconomic status and immune aging in older US adults in the health and retirement study.}, journal = {Biodemography and Social Biology}, volume = {67}, year = {2022}, pages = {187-202}, abstract = {

Socioeconomic and demographic factors including educational attainment, race and ethnicity, and childhood socioeconomic status (SES) are powerful predictors of inequalities in aging, morbidity, and mortality. Immune aging, including accumulation of late-differentiated, senescent-like lymphocytes and lower levels of na{\"\i}ve lymphocytes, may play a role in the development of the age-related health inequalities. This study used nationally representative data from more than 9,000 US adults from the Health and Retirement Study to investigate associations between educational attainment, race and ethnicity, and childhood SES and lymphocyte percentages. Respondents with lower educational attainment, Hispanic adults, and those who had a parent with less than a high school education had lymphocyte percentages consistent with more immune aging compared to those with greater educational attainment, non-Hispanic White adults, and respondents who had parents with a high school education, respectively. Associations between education, Hispanic ethnicity, and parents{\textquoteright} education and late differentiated senescent-like T lymphocytes (TemRA) and B cells were largely driven by cytomegalovirus (CMV), suggesting it is a factor in observed SES inequalities in immunosenescence. Na{\"\i}ve T lymphocytes may be particularly affected by socioeconomic position and may therefore be of particular interest to research interested in inequalities in health and aging.

}, keywords = {Child, Educational Status, ethnicity, Hispanic or Latino, Retirement, Social Class}, issn = {1948-5573}, doi = {10.1080/19485565.2022.2149465}, author = {Klopack, Eric T and Bharat Thyagarajan and Jessica Faul and Meier, Helen C S and Ramasubramanian, Ramya and Jung K Kim and Crimmins, Eileen M} } @article {12054, title = {Association of GrimAge DNA methylation components and 2-year mortality in the Health and Retirement Study }, journal = {Innovation in Aging}, volume = {5}, year = {2021}, pages = {675}, abstract = {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.}, keywords = {2-year mortality, DNA Methylation, GrimAge}, doi = {https://doi.org/10.1093/geroni/igab046.2525}, author = {Meier, Helen and Colter Mitchell and Eileen M. Crimmins and Bharat Thyagarajan and Jessica Faul} } @article {11384, title = {Associations of Age, Sex, Race/Ethnicity and Education with 13 Epigenetic Clocks in a Nationally Representative US Sample: The Health and Retirement Study.}, journal = {The Journals of Gerontology: Series A }, volume = {76}, year = {2021}, pages = {1117-1123}, abstract = {

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.

}, keywords = {DNA Methylation, DunedinPoAm38, Epigenetic Age, GrimAge, PhenoAgeAcceleration}, issn = {1758-535X}, doi = {10.1093/gerona/glab016}, author = {Eileen M. Crimmins and Bharat Thyagarajan and Morgan E. Levine and David R Weir and Jessica Faul} } @article {12053, title = {Epigenome Wide Associations of Smoking Behavior in the Health and Retirement Study}, journal = {Innovation in Aging}, volume = {5}, year = {2021}, pages = {668}, abstract = {DNA methylation (DNAm) is an increasingly popular biomarker of health and aging outcomes. Smoking behaviors have a significant and well documented correlation with methylation signatures within the epigenome and are important confounding variables to account for in epigenome-wide association studies (EWAS). However, the common classification of individuals as {\textquoteleft}current{\textquoteright}, {\textquoteleft}former{\textquoteright}, and {\textquoteleft}never{\textquoteright} smokers may miss crucial DNAm patterns associated with other smoking behaviors such as duration, intensity, and frequency of cigarette smoking, resulting in an underestimation of the contribution of smoking behaviors to DNAm and potentially biasing EWAS results. We investigated associations between multiple smoking behavioral phenotypes (smoking pack years, smoking duration, smoking start age, and smoking end age) and single site DNAm using linear regressions adjusting for age, sex, race/ethnicity, education, and cell-type proportions in a subsample of individuals who participated in the HRS 2016 Venous Blood Study (N=1,775). DNAm was measured using the Infinium Methylation EPIC BeadChip. All 4 phenotypes had significant associations (FDR < 0.05) with many methylation sites (packyears=6859, smoking duration=6572, start age=11374, quit age=773). There was not much overlap in DNAm sites between the full set of models with only 6 overlapping between all 4. However, the phenotypes packyears and smoking duration showed large overlap (N=3782). Results suggest additional smoking phenotypes beyond current/former/never smoker classification should be included in EWAS analyses to appropriately account for the influence of smoking behaviors on DNAm.}, keywords = {DNA Methylation, epigenome-wide association studies, Smoking}, doi = {https://doi.org/10.1093/geroni/igab046.2503}, author = {Fisher, Jonah and Meier, Helen and Jessica Faul and Colter Mitchell and Eileen M. Crimmins and Bharat Thyagarajan} } @article {11422, title = {Quest for a summary measure of biological age: The Health and Retirement Study.}, journal = {Geroscience}, volume = {43}, year = {2021}, pages = {395-408}, abstract = {

Measures of biological age and its components have been shown to provide important information about individual health and prospective change in health as there is clear value in being able to assess whether someone is experiencing accelerated or decelerated aging. However, how to best assess biological age remains a question. We compare prediction of health outcomes using existing summary measures of biological age with a measure created by adding novel biomarkers related to aging to measures based on more conventional clinical chemistry and exam measures. We also compare the explanatory power of summary biological age measures compared to the individual biomarkers used to construct the measures. To accomplish this, we examine how well biological age, phenotypic age, and expanded biological age and five sets of individual biomarkers explain variability in four major health outcomes linked to aging in a large, nationally representative cohort of older Americans. We conclude that different summary measures of accelerated aging do better at explaining different health outcomes, and that chronological age has greater explanatory power for both cognitive dysfunction and mortality than the summary measures. In addition, we find that there is reduction in the variance explained in health outcomes when indicators are combined into summary measures, and that combining clinical indicators with more novel markers related to aging does best at explaining health outcomes. Finally, it is hard to define a set of assays that parsimoniously explains the greatest amount of variance across the range of health outcomes studied here. All of the individual markers considered were related to at least one of the health outcomes.

}, keywords = {Biological age, Biomarkers, Phenotypic age, TAME markers}, issn = {2509-2723}, doi = {10.1007/s11357-021-00325-1}, author = {Eileen M. Crimmins and Bharat Thyagarajan and Jung K Kim and David R Weir and Jessica Faul} } @article {10828, title = {Validation of a hybrid approach to standardize immunophenotyping analysis in large population studies: The Health and Retirement Study}, journal = {Scientific Reports}, volume = {10}, year = {2020}, pages = {8759}, abstract = {Traditional manual gating strategies are often time-intensive, place a high burden on the analyzer, and are susceptible to bias between analyzers. Several automated gating methods have shown to exceed performance of manual gating for a limited number of cell subsets. However, many of the automated algorithms still require significant manual interventions or have yet to demonstrate their utility in large datasets. Therefore, we developed an approach that utilizes a previously published automated algorithm (OpenCyto framework) with a manually created hierarchically cell gating template implemented, along with a custom developed visualization software (FlowAnnotator) to rapidly and efficiently analyze immunophenotyping data in large population studies. This approach allows pre-defining populations that can be analyzed solely by automated analysis and incorporating manual refinement for smaller downstream populations. We validated this method with traditional manual gating strategies for 24 subsets of T cells, B cells, NK cells, monocytes and dendritic cells in 931 participants from the Health and Retirement Study (HRS). Our results show a high degree of correlation (r >= 0.80) for 18 (78\%) of the 24 cell subsets. For the remaining subsets, the correlation was low (<0.80) primarily because of the low numbers of events recorded in these subsets. The mean difference in the absolute counts between the hybrid method and manual gating strategy of these cell subsets showed results that were very similar to the traditional manual gating method. We describe a practical method for standardization of immunophenotyping methods in large scale population studies that provides a rapid, accurate and reproducible alternative to labor intensive manual gating strategies.}, keywords = {Bioinformatics, high-throughput screening}, isbn = {2045-2322}, doi = {10.1038/s41598-020-65016-x}, author = {Hunter-Schlichting, DeVon and Lane, John and Cole, Benjamin and Flaten, Zachary and Barcelo, Helene and Ramasubramanian, Ramya and Cassidy, Erin and Jessica Faul and Eileen M. Crimmins and Pankratz, Nathan and Bharat Thyagarajan} } @article {10426, title = {COMBINED EFFECT OF CMV SEROPOSITIVITY AND SYSTEMIC INFLAMMATION ON DEMENTIA PREVALENCE IN CANCER SURVIVORS}, journal = {Innovation in Aging}, volume = {3}, year = {2019}, pages = {S461-S461}, abstract = {Though cancer patients treated with multi-modal therapies demonstrate higher levels of systemic inflammation, which is associated with dementia, cancer survivors have not shown a consistent association with dementia. Since several studies reported an independent association between cytomegalovirus (CMV) infection, inflammation and dementia in non-cancer populations, we have evaluated whether CMV infection and systemic inflammation were associated with increased prevalence of dementia in cancer survivors in Health and Retirement Study (HRS). We evaluated prevalence of dementia (using score <=7 on the 27-point scale) among 1607 cancer survivors, in whom we measured CMV seropositivity and two biomarkers of systemic inflammation: C-reactive protein (CRP) and neutrophil-lymphocyte ratio (NLR). The prevalence of CMV seropositivity was 68.26\% (n=1097), while prevalence of increased systemic inflammation [CRP \>5mg/L and NLR \>4] was 4.23\% (n=68). Using survey logistic regression, adjusted for age, race, gender, BMI (Body Mass Index) and sampling design, cancer survivors who were both CMV seropositive and had increased systemic inflammation had the highest odds of dementia compared to those who were CMV seronegative and had low levels of systemic inflammation (OR=6.59; 95\% CI [2.81, 15.44]; p\<.0001). Cancer survivors who were CMV seropositive without evidence of systemic inflammation had a lower but increased odds of dementia (OR=2.02; 95\% CI [1.17, 3.47]; p=0.01). Odds of dementia among those who were CMV seronegative with elevated systemic inflammation was not significant (p=0.09). Our study demonstrates a possible role for ongoing CMV induced inflammation in determining dementia prevalence among cancer survivors that needs further confirmation.}, keywords = {Cancer, cnv, Dementia, Inflammation, seropositivity}, issn = {2399-5300}, doi = {10.1093/geroni/igz038.1724}, author = {Vivek, Sithara and Bharat Thyagarajan and Heather Hammond Nelson and Anna Prizment and Eileen M. Crimmins and Jessica Faul} } @article {10359, title = {How Does Subjective Age Get {\textquotedblleft}Under the Skin{\textquotedblright}? The Association Between Biomarkers and Feeling Older or Younger Than One{\textquoteright}s Age: The Health and Retirement Study}, journal = {Innovation in Aging}, volume = {3}, year = {2019}, pages = {igz035}, abstract = {Though subjective age is a well-recognized risk factor for several chronic diseases, the biological basis for these associations remains poorly understood.We used new comprehensive biomarker data from the 2016 wave of the nationally representative Health and Retirement Study (HRS) to evaluate the association between biomarker levels and self-reported subjective age in a subset of 3,740 HRS participants who provided a blood sample. We measured biomarkers in seven biological domains associated with aging: inflammation, glycemia, lipids, liver function, endocrine function, renal function, and cardiac function. The primary outcome was the age discrepancy score (subjective age - chronological age) categorized as those who felt younger, older, or the same as their chronological age (reference group). Analyses adjusted for comprehensive psychosocial factors (chronic stress index, depression score), demographic factors (race, sex, body mass index, marital status, physical activity), and prevalence of chronic health conditions (comorbidity index).The prevalence of clinically relevant reduced levels of albumin concentrations was lower in those who felt younger (8.8\% vs. 16.0\%; p = .006) and higher in those who felt older (20.4\% vs. 16.0\%; p = .03) when compared with the reference category. The prevalence of clinically significant elevation in liver enzymes such as alanine aminotransferase was also significantly lower among those who felt younger (7.1\% vs. 8.6\%; p = .04) when compared with the reference category. Prevalence of clinically elevated levels in cystatin C was also lower among those who felt younger when compared with the reference category (50.0\% vs. 59.1\%; p = .04). There was no association between lipids, glucose, or C-reactive protein (inflammatory marker) and subjective age categories.These results suggest that people who feel younger may have favorable biomarker profiles and as a result may have lower prevalence of age-related diseases when compared with those who feel older or those who feel the same as their chronological age.}, keywords = {Age discrepancy score, Biological domains, Physiological aging}, issn = {2399-5300}, doi = {10.1093/geroni/igz035}, author = {Bharat Thyagarajan and Shippee, Nathan and Parsons, Helen and Vivek, Sithara and Eileen M. Crimmins and Jessica Faul and Shippee, Tetyana} } @article {11949, title = {Effect of delayed cell processing and cryopreservation on immunophenotyping in multicenter population studies.}, journal = {Journal of Immunological Methods}, volume = {463}, year = {2018}, pages = {61-70}, abstract = {

Variability induced by delayed cell processing and cell cryopreservation presents unique challenges for immunophenotyping in large population studies. We conducted a pilot study to evaluate the effect of delayed cell processing and cryopreservation on cell percentages obtained by immunophenotyping. We collected blood from 20 volunteers and compared the effect of (a) delayed cell processing up to 72 h (b) cryopreservation and (c) the combined effect of delayed cell processing and cryopreservation on immunophenotyping of 31 cell subsets that included several subsets of T, B, Natural Killer (NK) cells, monocytes and dendritic cells using both whole blood collected in EDTA tubes and peripheral blood mononuclear cells collected in CPT tubes. We found the delayed cell processing up to 72 h or cryopreservation alone did not significantly affect the percentages T cells, dendritic cells or monocytes but significantly increased the percentage of B cells and NK cells (p for trend <=0.01) but. However combination of delayed cell processing up to 72 h and cryopreservation significantly increased the percentage of T cells as compared to cells processed immediately (p for trend <0.0001) while a delayed cell processing followed by cryopreservation decreased the percentage of NK cells (p for trend <0.0001). Total B-cells increased significantly with a 24-48 h delay in cell processing and cryopreservation but not at 72 h. The percentages of monocytes and dendritic cells remained unaffected by the combination of delayed cell processing and cryopreservation. These findings suggest that immunophenotyping of several immune cell subsets can be successfully implemented in large population studies as long as blood is processed within 48 h of biospecimen collection though some cell subsets may be more susceptible to a combination of delayed cell processing and cryopreservation.

}, keywords = {Cell Separation, Cryopreservation, Immunophenotyping, Leukocytes, Time Factors}, issn = {1872-7905}, doi = {10.1016/j.jim.2018.09.007}, author = {Bharat Thyagarajan and Barcelo, Helene and Eileen M. Crimmins and David R Weir and Minnerath, Sharon and Vivek, Sithara and Jessica Faul} } @article {9814, title = {A Practical Cryopreservation and Staining Protocol for Immunophenotyping in Population Studies.}, journal = {Current Protocols in Cytometry}, volume = {84}, year = {2018}, month = {04/2018}, pages = {e35}, abstract = {Large population-based cohort studies, through their prospective collection of a broad range of health information, represent an invaluable resource for novel insights into the pathogenesis of human diseases. Collection and cryopreservation of viable cells from blood samples is becoming increasingly common in large cohorts as these cells are a valuable resource for immunophenotyping and functional studies. The cryopreservation of peripheral blood mononuclear cells (PBMCs), thawing, and immunophenotyping protocols used to immunophenotype 9938 participants in the Health and Retirement Study (HRS) are described. The extensive quality control involved in a large-scale immunophenotyping epidemiological study is also outlined. The existing literature on the effect of cryopreservation on various immune cell subsets including T, B, NK cells, monocytes, and dendritic cells is provided. {\textcopyright} 2018 by John Wiley \& Sons, Inc.}, keywords = {Cryopreservation, Quality control, Survey Methodology}, issn = {1934-9300}, doi = {10.1002/cpcy.35}, author = {Barcelo, Helene and Jessica Faul and Eileen M. Crimmins and Bharat Thyagarajan} } @article {9065, title = {Venous Blood Collection and Assay Protocol in the 2016 Health and Retirement Study}, year = {2017}, institution = {Survey Research Center, Institute for Social Research, University of Michigan}, address = {Ann Arbor, Michigan}, author = {Eileen M. Crimmins and Jessica Faul and Bharat Thyagarajan and David R Weir} }