Gut microbiota, blood metabolites, and left ventricular diastolic dysfunction in US Hispanics/Latinos.

BACKGROUND: Left ventricular diastolic dysfunction (LVDD) is an important precursor of heart failure (HF), but little is known about its relationship with gut dysbiosis and microbial-related metabolites. By leveraging the multi-omics data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a study with population at high burden of LVDD, we aimed to characterize gut microbiota associated with LVDD and identify metabolite signatures of gut dysbiosis and incident LVDD. RESULTS: We included up to 1996 Hispanic/Latino adults (mean age: 59.4 years; 67.1% female) with comprehensive echocardiography assessments, gut microbiome, and blood metabolome data. LVDD was defined through a composite criterion involving tissue Doppler assessment and left atrial volume index measurements. Among 1996 participants, 916 (45.9%) had prevalent LVDD, and 212 out of 594 participants without LVDD at baseline developed incident LVDD over a median 4.3 years of follow-up. Using multivariable-adjusted analysis of compositions of microbiomes (ANCOM-II) method, we identified 7 out of 512 dominant gut bacterial species (prevalence > 20%) associated with prevalent LVDD (FDR-q < 0.1), with inverse associations being found for Intestinimonas_massiliensis, Clostridium_phoceensis, and Bacteroide_coprocola and positive associations for Gardnerella_vaginali, Acidaminococcus_fermentans, Pseudomonas_aeruginosa, and Necropsobacter_massiliensis. Using multivariable adjusted linear regression, 220 out of 669 circulating metabolites with detection rate > 75% were associated with the identified LVDD-related bacterial species (FDR-q < 0.1), with the majority being linked to Intestinimonas_massiliensis, Clostridium_phoceensis, and Acidaminococcus_fermentans. Furthermore, 46 of these bacteria-associated metabolites, mostly glycerophospholipids, secondary bile acids, and amino acids, were associated with prevalent LVDD (FDR-q < 0.1), 21 of which were associated with incident LVDD (relative risk ranging from 0.81 [p = 0.001, for guanidinoacetate] to 1.25 [p = 9 × 10-5, for 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4)]). The inclusion of these 21 bacterial-related metabolites significantly improved the prediction of incident LVDD compared with a traditional risk factor model (the area under the receiver operating characteristic curve [AUC] = 0.73 vs 0.70, p = 0.001). Metabolite-based proxy association analyses revealed the inverse associations of Intestinimonas_massilliensis and Clostridium_phoceensis and the positive association of Acidaminococcus_fermentans with incident LVDD. CONCLUSION: In this study of US Hispanics/Latinos, we identified multiple gut bacteria and related metabolites linked to LVDD, suggesting their potential roles in this preclinical HF entity. Video Abstract.

Thyroid-related Hormones and Hypertension Incidence in Middle-Aged and Older Hispanic/Latino Adults: The HCHS/SOL Study.

Background: Thyroid-related hormones act to regulate metabolic pathways and blood pressure (BP). However, the relationship of TSH and peripheral thyroid hormones and the role of the hypothalamic-pituitary-thyroid axis on hypertension development is not fully understood. We assessed sex-specific associations of thyroid-related hormones with BP and hypertension in Hispanic/Latino adults followed for 6 years. Methods: We studied 1789 adults, ages 45 to 74, free of diabetes at baseline from a subcohort of the Hispanic Community Health Study/Study of Latinos. We assessed TSH, free T4 (FT4), T3, and various indicators of thyroid axis. Using multivariable linear and Poisson regression adjusted for survey design and confounding variables, we estimated a priori sex-specific associations of thyroid-related hormones with changes in BP and hypertension development. Results: In men and women, TSH and TSH/FT4 ratios were associated with changes in diastolic BP and T3 with changes in pulse pressure and the development of hypertension from prehypertension. In men, a 1-SD increase in TSH [incident rate ratio (IRR) = 1.42; 95% confidence interval (CI): 1.15, 1.75] and TSH/FT4 ratio (IRR = 1.20; 95% CI: 1.07, 1.35) were positively associated with the development of hypertension from prehypertension while the TSH/FT4 ratio (IRR = 0.85; 95% CI: .72, 1.00) was protective in women. We observed sex-specific differences in associations of the T3/FT4 ratio and indices of pituitary sensitivity to thyroid hormones with changes in pulse pressure and hypertension development. Conclusion: Thyroid-related hormones are associated with sex-specific changes in BP and hypertension among Hispanic/Latino adults consistent with selected studies conducted in other populations. Mechanisms underlying associations of pituitary sensitivity to thyroid hormones with BP and hypertension development warrant further study.

Thyroid Hormones and Diabetes in Euthyroid Hispanic/Latino Adults of Diverse Backgrounds: HCHS/SOL.

Context: Previous studies have demonstrated associations of endogenous thyroid hormones with diabetes; less is known about stages of diabetes development at which they are operative, mechanisms of associations, and the role of the hypothalamic-pituitary-thyroid axis. Objective: This study examined associations of thyroid hormones with incident prediabetes and diabetes and with changes in glycemic traits in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), the largest cohort of Hispanic/Latino adults with diverse backgrounds in the United States. Methods: The study includes 592 postmenopausal euthyroid women and 868 euthyroid men aged 45 to 74 years without diabetes at baseline participating in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Baseline hormones included thyrotropin (TSH), free thyroxine (FT4), total triiodothyronine (T3), and indices calculated from thyroid hormones evaluating pituitary sensitivity to thyroid hormone. Transitions to diabetes and prediabetes, and changes in glycemic traits determined at the 6-year follow-up visit, were examined using multivariable Poisson and linear regressions. Results: Among women, T3 (incident rate ratio [IRR] = 1.65; 95% CI, 1.22-2.24; P = .001) and TSH (IRR = 2.09; 95% CI, 1.01-4.33; P = .047) were positively, while FT4 (IRR = 0.59; 95% CI, 0.39-0.88; P = .011) was inversely, associated with transition from prediabetes to diabetes. Among men, the T3/FT4 ratio was positively associated with transition from normoglycemia to prediabetes but not from prediabetes to diabetes. Indices measuring sensitivity of the pituitary to thyroid hormone suggested increased sensitivity in men who transitioned from prediabetes to diabetes. Conclusion: Positive associations in women of T3 and TSH and inverse associations of FT4, as well as inverse associations of thyroid indices in men with transition from prediabetes to diabetes, but not from normoglycemia to diabetes, suggest decreased pituitary sensitivity to thyroid hormones in women and increased sensitivity in men later in the development of diabetes.

Early Life Stress Is Associated with Alterations in Lymphocyte Subsets Independent of Increased Inflammation in Adolescents.

Early life stress (ELS) is linked to an elevated risk of poor health and early mortality, with emerging evidence pointing to the pivotal role of the immune system in long-term health outcomes. While recent research has focused on the impact of ELS on inflammation, this study examined the impact of ELS on immune function, including CMV seropositivity, inflammatory cytokines, and lymphocyte cell subsets in an adolescent cohort. This study used data from the Early Life Stress and Cardiometabolic Health in Adolescence Study (N = 191, aged 12 to 21 years, N = 95 exposed to ELS). We employed multiple regression to investigate the association between ELS, characterized by early institutional care, cytomegalovirus (CMV) seropositivity (determined by chemiluminescent immunoassay), inflammation (CRP, IL-6, and TNF-a determined by ELISA), and twenty-one immune cell subsets characterized by flow cytometry (sixteen T cell subsets and five B cell subsets). Results reveal a significant association between ELS and lymphocytes that was independent of the association between ELS and inflammation: ELS was associated with increased effector memory helper T cells, effector memory cytotoxic T cells, senescent T cells, senescent B cells, and IgD- memory B cells compared to non-adopted youth. ELS was also associated with reduced percentages of helper T cells and naive cytotoxic T cells. Exploratory analyses found that the association between ELS and fewer helper T cells and increased cytotoxic T cells remained even in cytomegalovirus (CMV) seronegative youth. These findings suggest that ELS is associated with cell subsets that are linked to early mortality risk in older populations and markers of replicative senescence, separate from inflammation, in adolescents.

Accelerated Aging in Cancer Survivors: Cellular Senescence, Frailty, and Possible Opportunities for Interventions.

The population of cancer survivors has markedly increased due to the rapid improvements in cancer treatment. However, cancer survivors experience accelerated aging, which leads to chronic diseases and other age-related conditions, such as frailty. Those conditions may persist years after cancer diagnosis and treatment. Cellular senescence, a hallmark of aging, is one of the mechanisms that contribute to accelerated aging in cancer survivors. Several aging measures, including measures based on clinical markers and biomarkers, have been proposed to estimate the aging process, and some of them have shown associations with mortality and frailty in cancer survivors. Several anti-aging interventions, including lifestyle changes and anti-aging drugs, have been proposed. Future research, particularly in large-scale studies, is needed to determine the efficiency of these aging measures and anti-aging interventions before considering their application in clinics. This review focuses on the mechanisms of cellular senescence and accelerated aging in cancer survivors, assessment of the aging process using clinical markers and biomarkers, and the high prevalence of frailty in that population, as well as possible opportunities for anti-aging interventions. A deeper understanding of aging measures and anti-aging interventions in cancer survivors will contribute to the development of effective strategies to mitigate accelerated aging in cancer survivors and improve their quality of life.

Gut Microbiota and Blood Metabolites Related to Fiber Intake and Type 2 Diabetes.

BACKGROUND: Consistent evidence suggests diabetes-protective effects of dietary fiber intake. However, the underlying mechanisms, particularly the role of gut microbiota and host circulating metabolites, are not fully understood. We aimed to investigate gut microbiota and circulating metabolites associated with dietary fiber intake and their relationships with type 2 diabetes (T2D). METHODS: This study included up to 11 394 participants from the HCHS/SOL (Hispanic Community Health Study/Study of Latinos). Diet was assessed with two 24-hour dietary recalls at baseline. We examined associations of dietary fiber intake with gut microbiome measured by shotgun metagenomics (350 species/85 genera and 1958 enzymes; n=2992 at visit 2), serum metabolome measured by untargeted metabolomics (624 metabolites; n=6198 at baseline), and associations between fiber-related gut bacteria and metabolites (n=804 at visit 2). We examined prospective associations of serum microbial-associated metabolites (n=3579 at baseline) with incident T2D over 6 years. RESULTS: We identified multiple bacterial genera, species, and related enzymes associated with fiber intake. Several bacteria (eg, Butyrivibrio, Faecalibacterium) and enzymes involved in fiber degradation (eg, xylanase EC3.2.1.156) were positively associated with fiber intake, inversely associated with prevalent T2D, and favorably associated with T2D-related metabolic traits. We identified 159 metabolites associated with fiber intake, 47 of which were associated with incident T2D. We identified 18 of these 47 metabolites associated with the identified fiber-related bacteria, including several microbial metabolites (eg, indolepropionate and 3-phenylpropionate) inversely associated with the risk of T2D. Both Butyrivibrio and Faecalibacterium were associated with these favorable metabolites. The associations of fiber-related bacteria, especially Faecalibacterium and Butyrivibrio, with T2D were attenuated after further adjustment for these microbial metabolites. CONCLUSIONS: Among United States Hispanics/Latinos, dietary fiber intake was associated with favorable profiles of gut microbiota and circulating metabolites for T2D. These findings advance our understanding of the role of gut microbiota and microbial metabolites in the relationship between diet and T2D.

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.

Whole genome-wide sequence analysis of long-lived families (Long-Life Family Study) identifies MTUS2 gene associated with late-onset Alzheimer's disease.

INTRODUCTION: Late-onset Alzheimer's disease (LOAD) has a strong genetic component. Participants in Long-Life Family Study (LLFS) exhibit delayed onset of dementia, offering a unique opportunity to investigate LOAD genetics. METHODS: We conducted a whole genome sequence analysis of 3475 LLFS members. Genetic associations were examined in six independent studies (N = 14,260) with a wide range of LOAD risk. Association analysis in a sub-sample of the LLFS cohort (N = 1739) evaluated the association of LOAD variants with beta amyloid (Aß) levels. RESULTS: We identified several single nucleotide polymorphisms (SNPs) in tight linkage disequilibrium within the MTUS2 gene associated with LOAD (rs73154407, p = 7.6 × 10-9). Association of MTUS2 variants with LOAD was observed in the five independent studies and was significantly stronger within high levels of Aß42/40 ratio compared to lower amyloid. DISCUSSION: MTUS2 encodes a microtubule associated protein implicated in the development and function of the nervous system, making it a plausible candidate to investigate LOAD biology. HIGHLIGHTS: Long-Life Family Study (LLFS) families may harbor late onset Alzheimer's dementia (LOAD) variants. LLFS whole genome sequence analysis identified MTUS2 gene variants associated with LOAD. The observed LLFS variants generalized to cohorts with wide range of LOAD risk. The association of MTUS2 with LOAD was stronger within high levels of beta amyloid. Our results provide evidence for MTUS2 gene as a novel LOAD candidate locus.

Targeted electronic health record-based recruitment strategy to enhance COVID-19 vaccine response clinical research study enrollment.

Efficient recruitment of eligible participants is a significant challenge for clinical research studies. This challenge was exacerbated during the COVID-19 pandemic when in-person recruitment was not an option. In 2020, the University of Minnesota was tasked, as part of the National Cancer Institute's Serological Sciences Network for COVID-19 (SeroNet), to recruit participants for a longitudinal serosurveillance clinical research study with a goal of characterizing the COVID-19 vaccine-elicited immune response among immunocompromised individuals, which necessitated reliance on non-traditional strategies for participant recruitment. To meet our enrollment target of 300 transplant patients, 300 cancer patients, 100 persons living with HIV, and 200 immunocompetent individuals, we utilized targeted electronic health record (EHR)-based recruitment in addition to traditional recruitment tools, which was an effective combination of recruitment strategies. A significant advantage of patient portal messaging or other digital recruitment strategies such as email communication is timing. We reached 85 % (769 out of 900) of our enrollment target within one year with a 14.3 % response rate to invitations to participate in our study. This achievement is perhaps more salient given the COVID-19 pandemic-related constraints within which we were operating. We demonstrated that the EHR can be leveraged to quickly identify potentially eligible study participants either via EHR communication or mail. We also illustrate how the online portal MyChart can be used to efficiently send targeted recruitment messages.

Proteomic Biomarkers of Quantitative Interstitial Abnormalities in COPDGene and CARDIA Lung Study.

Rationale: Quantitative interstitial abnormalities (QIAs) are early measures of lung injury automatically detected on chest computed tomography scans. QIAs are associated with impaired respiratory health and share features with advanced lung diseases, but their biological underpinnings are not well understood. Objectives: To identify novel protein biomarkers of QIAs using high-throughput plasma proteomic panels within two multicenter cohorts. Methods: We measured the plasma proteomics of 4,383 participants in an older, ever-smoker cohort (COPDGene [Genetic Epidemiology of Chronic Obstructive Pulmonary Disease]) and 2,925 participants in a younger population cohort (CARDIA [Coronary Artery Disease Risk in Young Adults]) using the SomaLogic SomaScan assays. We measured QIAs using a local density histogram method. We assessed the associations between proteomic biomarker concentrations and QIAs using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, and study center (Benjamini-Hochberg false discovery rate-corrected P ⩽ 0.05). Measurements and Main Results: In total, 852 proteins were significantly associated with QIAs in COPDGene and 185 in CARDIA. Of the 144 proteins that overlapped between COPDGene and CARDIA, all but one shared directionalities and magnitudes. These proteins were enriched for 49 Gene Ontology pathways, including biological processes in inflammatory response, cell adhesion, immune response, ERK1/2 regulation, and signaling; cellular components in extracellular regions; and molecular functions including calcium ion and heparin binding. Conclusions: We identified the proteomic biomarkers of QIAs in an older, smoking population with a higher prevalence of pulmonary disease and in a younger, healthier community cohort. These proteomics features may be markers of early precursors of advanced lung diseases.

Connections between reproductive health and cognitive aging among women enrolled in the HCHS/SOL and SOL-INCA.

INTRODUCTION: Reproductive health history may contribute to cognitive aging and risk for Alzheimer's disease, but this is understudied among Hispanic/Latina women. METHODS: Participants included 2126 Hispanic/Latina postmenopausal women (44 to 75 years) from the Study of Latinos-Investigation of Neurocognitive Aging. Survey linear regressions separately modeled the associations between reproductive health measures (age at menarche, history of oral contraceptive use, number of pregnancies, number of live births, age at menopause, female hormone use at Visit 1, and reproductive span) with cognitive outcomes at Visit 2 (performance, 7-year change, and mild cognitive impairment [MCI] prevalence). RESULTS: Younger age at menarche, oral contraceptive use, lower pregnancies, lower live births, and older age at menopause were associated with better cognitive performance. Older age at menarche was protective against cognitive change. Hormone use was linked to lower MCI prevalence. DISCUSSION: Several aspects of reproductive health appear to impact cognitive aging among Hispanic/Latina women.

Immune cells are associated with mortality: the Health and Retirement Study.

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.

Explainable variational autoencoder (E-VAE) model using genome-wide SNPs to predict dementia.

OBJECTIVE: Alzheimer's disease (AD) and AD related dementias (ADRD) are complex multifactorial neurodegenerative diseases. The associations between genetic variants obtained from genome wide association studies (GWAS) are the most widely available and well documented variants associated with ADRD. Application of deep learning methods to analyze large scale GWAS data may be a powerful approach to elucidate the biological mechanisms in ADRD compared to penalized regression models that may lead to over-fitting. METHODS: We developed a deep learning frame work explainable variational autoencoder (E-VAE) classifier model using genotype (GWAS SNPs = 5474) data from 2714 study participants in the Health and Retirement Study (HRS) to classify ADRD. We validated the generalizability of this model among 234 participants in the Religious Orders Study and Memory and Aging Project (ROSMAP). Utilizing a linear decoder approach we have extracted the weights associated with latent features for biological interpretation. RESULTS: We obtained a predictive accuracy of 0.71 (95 % CI [0.59, 0.84]) with an AUC of 0.69 in the HRS test dataset and got an accuracy of 0.62 (95 % CI [0.56, 0.68]) with an AUC of 0.63 in the ROSMAP dataset. CONCLUSION: This is the first study showing the generalizability of a deep learning prediction model for dementia using genetic variants in an independent cohort. The latent features identified using E-VAE can help us understand the biology of AD/ ADRD and better characterize disease status.

Association Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk.

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). P<0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1-SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04-1.12; P<0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (ß=0.091; P=0.11) or in the reverse direction (ß=-0.012; P=0.076). Additional bidirectional Mendelian randomization analyses revealed that low-density lipoprotein cholesterol had a causal effect on mtDNA CN (ß=-0.084; P<0.001), but the reverse direction was not significant (P=0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low-density lipoprotein cholesterol level (P=0.52), whereas there was a strong direct causal effect of higher low-density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (ß=-0.092; P<0.001). Conclusions Our findings indicate that high low-density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.

Aging measures and cancer: Findings from the Health and Retirement Study.

Background: Compared to cancer-free persons, cancer survivors of the same chronological age (CA) have increased physiological dysfunction, i.e., higher biological age (BA), which may lead to higher morbidity and mortality. We estimated BA using eight aging metrics: BA computed by Klemera Doubal method (KDM-BA), phenotypic age (PhenoAge), five epigenetic clocks (ECs, Horvath, Hannum, Levine, GrimAge, and pace of aging (POA)), and subjective age (SA). We tested if aging constructs were associated with total cancer prevalence and all-cause mortality in cancer survivors and controls, i.e., cancer-free persons, in the Health and Retirement Study (HRS), a large population-based study. Methods: In 2016, data on BA-KDM, PhenoAge, and SA were available for 946 cancer survivors and 4,555 controls; data for the five ECs were available for 582 cancer survivors and 2,805 controls. Weighted logistic regression was used to estimate the association between each aging construct and cancer prevalence (odds ratio, OR, 95%CI). Weighted Cox proportional hazards regression was used to estimate the associations between each aging construct and cancer incidence as well as all-cause mortality (hazard ratio, HR, 95%CI). To study all BA metrics (except for POA) independent of CA, we estimated age acceleration as residuals of BA regressed on CA. Results: Age acceleration for each aging construct and POA were higher in cancer survivors than controls. In a multivariable-adjusted model, five aging constructs (age acceleration for Hannum, Horvath, Levine, GrimAge, and SA) were associated with cancer prevalence. Among all cancer survivors, age acceleration for PhenoAge and four ECs (Hannum, Horvath, Levine, and GrimAge), was associated with higher all-cause mortality over 4 years of follow-up. PhenoAge, Hannum, and GrimAge were also associated with all-cause mortality in controls. The highest HR was observed for GrimAge acceleration in cancer survivors: 2.03 (95% CI, 1.58-2.60). In contrast, acceleration for KDM-BA and POA was significantly associated with mortality in controls but not in cancer survivors. When all eight aging constructs were included in the same model, two of them (Levine and GrimAge) were significantly associated with mortality among cancers survivors. None of the aging constructs were associated with cancer incidence. Conclusion: Variations in the associations between aging constructs and mortality in cancer survivors and controls suggests that aging constructs may capture different aspects of aging and that cancer survivors may be experiencing age-related physiologic dysfunctions differently than controls. Future work should evaluate how these aging constructs predict mortality for specific cancer types.

Cohabitation as a determinant of adaptive and innate immune cell profiles: Findings from the Health and Retirement Study.

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 (±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.

Associations between GrimAge acceleration and pulmonary function in the Coronary Artery Risk Development in Young Adults (CARDIA) study.

Background: The objective of this research was to determine whether pulmonary function is associated with epigenetic aging (GrimAge) and whether GrimAge predicts emphysema. Methods: This prospective study examined 1042 participants enrolled as part of a community-based longitudinal cohort. The cross-sectional associations between pulmonary function and GrimAge, measured at study year (Y) 20 (participant ages 40-45 years), and prospective associations with emphysema at Y25 were examined. Results: At Y20, forced expiratory volume in 1 s (FEV1) and FEV1/forced vital capacity (FVC) were negatively associated with GrimAge; for Y0-Y10 cumulative measures, only the FEV1/FVC ratio was associated with GrimAge at Y15 and Y20. Emphysema at Y25 was associated with GrimAge at Y15 and Y20. Conclusion: Pulmonary function was associated with GrimAge during early and mid-life; GrimAge partially mediated the association between pulmonary function and emphysema.

Development and Characterization of Proteomic Aging Clocks in the Atherosclerosis Risk in Communities (ARIC) Study.

Biological age may be estimated by proteomic aging clocks (PACs). Previous published PACs were constructed either in smaller studies or mainly in White individuals, and they used proteomic measures from only one-time point. In the Atherosclerosis Risk in Communities (ARIC) study of about 12,000 persons followed for 30 years (around 75% White, 25% Black), we created de novo PACs and compared their performance to published PACs at two different time points. We measured 4,712 plasma proteins by SomaScan in 11,761 midlife participants, aged 46-70 years (1990-92), and 5,183 late-life pariticpants, aged 66-90 years (2011-13). All proteins were log2-transformed to correct for skewness. We created de novo PACs by training them against chronological age using elastic net regression in two-thirds of healthy participants in midlife and late life and compared their performance to three published PACs. We estimated age acceleration (by regressing each PAC on chronological age) and its change from midlife to late life. We examined their associations with mortality from all-cause, cardiovascular disease (CVD), cancer, and lower respiratory disease (LRD) using Cox proportional hazards regression in all remaining participants irrespective of health. The model was adjusted for chronological age, smoking, body mass index (BMI), and other confounders. The ARIC PACs had a slightly stronger correlation with chronological age than published PACs in healthy participants at each time point. Associations with mortality were similar for the ARIC and published PACs. For late-life and midlife age acceleration for the ARIC PACs, respectively, hazard ratios (HRs) per one standard deviation were 1.65 and 1.38 (both p<0.001) for all-cause mortality, 1.37 and 1.20 (both p<0.001) for CVD mortality, 1.21 (p=0.03) and 1.04 (p=0.19) for cancer mortality, and 1.46 and 1.68 (both p<0.001) for LRD mortality. For the change in age acceleration, HRs for all-cause, CVD, and LRD mortality were comparable to those observed for late-life age acceleration. The association between the change in age acceleration and cancer mortality was insignificant. In this prospective study, the ARIC and published PACs were similarly associated with an increased risk of mortality and advanced testing in relation to various age-related conditions in future studies is suggested.

Pre-Analytical Variables Influencing Stability of Blood-Based Biomarkers of Neuropathology.

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 4∘C, three freeze-thaw cycles, and a combination of 48-h processing delay when stored at 4∘C and three freeze-thaw cycles on biomarker stability. Using the Simoa assay (Quanterix Inc.), we measured amyloid-ß 40 (Aß40), amyloid-ß 42 (Aß42), neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and phosphorylated tau 181 (p-tau-181). RESULTS: We found that Aß40 and Aß42 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 Aß42/40 ratio remained stable with a processing delay up to 48 h while plasma Aß42/40 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.