Atherosclerosis Risk In Communities Research Articles

Incident heart failure in chronic kidney disease: proteomics informs biology and risk stratification.

Incident heart failure (HF) among individuals with chronic kidney disease (CKD) incurs hospitalizations that burden patients and health care systems. There are few preventative therapies, and the Pooled Cohort equations to Prevent Heart Failure (PCP-HF) perform poorly in the setting of CKD. New drug targets and better risk stratification are urgently needed. In this analysis of incident HF, SomaScan V4.0 (4638 proteins) was analysed in 2906 participants of the Chronic Renal Insufficiency Cohort (CRIC) with validation in the Atherosclerosis Risk in Communities (ARIC) study. The primary outcome was 14-year incident HF (390 events); secondary outcomes included 4-year HF (183 events), HF with reduced ejection fraction (137 events), and HF with preserved ejection fraction (165 events). Mendelian randomization and Gene Ontology were applied to examine causality and pathways. The performance of novel multi-protein risk models was compared to the PCP-HF risk score. Over 200 proteins were associated with incident HF after adjustment for estimated glomerular filtration rate at P < 1 × 10-5. After adjustment for covariates including N-terminal pro-B-type natriuretic peptide, 17 proteins remained associated at P < 1 × 10-5. Mendelian randomization associations were found for six proteins, of which four are druggable targets: FCG2B, IGFBP3, CAH6, and ASGR1. For the primary outcome, the C-statistic (95% confidence interval [CI]) for the 48-protein model in CRIC was 0.790 (0.735, 0.844) vs. 0.703 (0.644, 0.762) for the PCP-HF model (P = .001). C-statistic (95% CI) for the protein model in ARIC was 0.747 (0.707, 0.787). Large-scale proteomics reveal novel circulating protein biomarkers and potential mediators of HF in CKD. Proteomic risk models improve upon the PCP-HF risk score in this population.

Association of Cumulative Systolic Blood Pressure with Left Atrial Function in the Setting of Normal Left Atrial Size: the Atherosclerosis Risk in Communities (ARIC) Study

Lower left atrial (LA) function is associated with increased risk for cardiovascular disease (CVD) events; data on risk factors for impaired LA function are limited. We evaluated the effect of cumulative systolic blood pressure (cSBP) from midlife to older age on LA strain in adults with normal LA size. We included participants in the Atherosclerosis Risk in Communities study with LA strain measured on the Visit 5 echocardiogram (2011-2013), excluding those with atrial fibrillation and LA volume index >34ml/m2. cSBP was calculated from Visit 1 (1987-1989) through Visit 5. Linear regression models were used to evaluate associations between cSBP and LA strain measures. 3,859 participants with mean (SD) age of 75.2 (5.0) years were included in the analysis; 725 (18.8%) Black and 2342 (60.7%) women. After adjusting for demographics, CVD risk factors, heart failure, and coronary heart disease, each 10mmHg higher cSBP was associated with 0.32% (95% CI -0.52%, -0.13%) and 0.37% (95% CI -0.51%, -0.22%) absolute reduction in LA reservoir and conduit strain, respectively. Associations were attenuated after adjustment for left ventricular (LV) systolic and diastolic function and mass (-0.12%; 95% CI, -0.31, 0.06 for reservoir strain and -0.24%; 95% CI -0.38%, -0.10% for conduit strain). In subgroup analyses, the association of cSBP with conduit strain was statistically significant among those with normal LV systolic and diastolic function. Cumulative exposure to elevated blood pressure from midlife to late life was modestly associated with lower LA reservoir and conduit strain in older adults with normal LA size, mostly related to the effect of blood pressure on LV function and mass. However, the association of cSBP and LA conduit strain in subgroups with normal LV function suggests that LA remodeling in response to hypertension occurs before LV dysfunction is detected on echocardiography.

A Comparison of PM2.5 Exposure Estimates from Different Estimation Methods and their Associations with Cognitive Testing and Brain MRI Outcomes

Reported associations between particulate matter with aerodynamic diameter < 2.5μm (PM2.5) and cognitive outcomes remain mixed. Differences in exposure estimation method may contribute to this heterogeneity. To assess agreement between PM2.5 exposure concentrations across 11 exposure estimation methods and to compare resulting associations between PM2.5 and cognitive or MRI outcomes. We used Visit 5 (2011-2013) cognitive testing and brain MRI data from the Atherosclerosis Risk in Communities (ARIC) Study. We derived address-linked average 2000-2007 PM2.5 exposure concentrations in areas immediately surrounding the four ARIC recruitment sites (Forsyth County, NC; Jackson, MS; suburbs of Minneapolis, MN; Washington County, MD) using 11 estimation methods. We assessed agreement between method-specific PM2.5 concentrations using descriptive statistics and plots, overall and by site. We used adjusted linear regression to estimate associations of method-specific PM2.5 exposure estimates with cognitive scores (n=4,678) and MRI outcomes (n=1,518) stratified by study site and combined site-specific estimates using meta-analyses to derive overall estimates. We explored the potential impact of unmeasured confounding by spatially patterned factors. Exposure estimates from most methods had high agreement across sites, but low agreement within sites. Within-site exposure variation was limited for some methods. Consistently null findings for the PM2.5-cognitive outcome associations regardless of method precluded empirical conclusions about the potential impact of method on study findings in contexts where positive associations are observed. Not accounting for study site led to consistent, adverse associations, regardless of exposure estimation method, suggesting the potential for substantial bias due to residual confounding by spatially patterned factors. PM2.5 estimation methods agreed across sites but not within sites. Choice of estimation method may impact findings when participants are concentrated in small geographic areas. Understanding unmeasured confounding by factors that are spatially patterned may be particularly important in studies of air pollution and cognitive or brain health.

Enhancing long-term survival prediction with two short-term events: Landmarking with a flexible varying coefficient model.

Patients with cardiovascular diseases who experience disease-related short-term events, such as hospitalizations, often exhibit diverse long-term survival outcomes compared to others. In this study, we aim to improve the prediction of long-term survival probability by incorporating two short-term events using a flexible varying coefficient landmark model. Our objective is to predict the long-term survival among patients who survived up to a pre-specified landmark time since the initial admission. Inverse probability weighting estimation equations are formed based on the information of the short-term outcomes before the landmark time. The kernel smoothing method with the use of cross-validation for bandwidth selection is employed to estimate the time-varying coefficients. The predictive performance of the proposed model is evaluated and compared using predictive measures: area under the receiver operating characteristic curve and Brier score. Simulation studies confirm that parameters under the landmark models can be estimated accurately and the predictive performance of the proposed method consistently outperforms existing methods that either do not incorporate or only partially incorporate information from two short-term events. We demonstrate the practical application of our model using a community-based cohort from the Atherosclerosis Risk in Communities (ARIC) study.

Glucose Color Index: Development and Validation of a Novel Measure of the Shape of Glycemic Variability.

Standard continuous glucose monitoring (CGM) metrics: mean glucose, standard deviation, coefficient of variation, and time in range, fail to capture the shape of variability in the CGM time series. This information could facilitate improved diabetes management. We analyzed CGM data from 141 adults with type 2 diabetes in the Hyperglycemic Profiles in Obstructive Sleep Apnea (HYPNOS) trial. Participants in HYPNOS wore CGM sensors for up to two weeks at two time points, three months apart. We calculated the log-periodogram for each time period, summarizing using disjoint linear models. These summaries were combined into a single value, termed the Glucose Color Index (GCI), using canonical correlation analysis. We compared the between-wear correlation of GCI with those of standard CGM metrics and assessed associations between GCI and diabetes comorbidities in 398 older adults with type 2 diabetes from the Atherosclerosis Risk in Communities (ARIC) study. The GCI achieved a test-retest correlation of R = .75. Adjusting for standard CGM metrics, the GCI test-retest correlation was R = .55. Glucose Color Index was significantly associated (p < .05) with impaired physical functioning, frailty/pre-frailty, cardiovascular disease, chronic kidney disease, and dementia/mild cognitive impairment after adjustment for confounders. We developed and validated the GCI, a novel CGM metric that captures the shape of glucose variability using the periodogram signal decomposition. Glucose Color Index was reliable within participants over a three-month period and associated with diabetes comorbidities. The GCI suggests a promising avenue toward the development of CGM metrics which more fully incorporate time series information.

Deep terminal negative of the P wave in V1 and incidence of ischemic stroke: The atherosclerosis risk in communities (ARIC) study

BackgroundDeep terminal negative of the P wave in V1 (DTNPV1) is a marker of left atrial remodeling. We aimed to evaluate the association of DTNPV1 with incident ischemic stroke. MethodsThe Atherosclerosis Risk in Communities study is a prospective community-based cohort study. All participants at visit 4 (1996–1998) except those with prevalent stroke, missing covariates, and missing or uninterpretable ECG were included. DTNPV1 was defined as the absolute value of the depth of the terminal negative phase >100 μV in the presence of biphasic P wave in V1. Association between DTNPV1 as a time-dependent exposure variable and incident ischemic stroke was evaluated. The accuracy of the prediction model consisting of DTNPV1 and CHA2DS2-VASc variables in predicting ischemic stroke was analyzed. ResultsAmong 10,605 participants (63 ± 6 years, 56% women, 20% Black), 803 cases of ischemic stroke occurred over a median follow-up of 20.19 years. After adjusting for demographics, DTNPV1 was associated with an increased risk of stroke (HR 1.96, [95% CI 1.39–2.77]). After further adjusting for stroke risk factors, use of aspirin and anticoagulants, and time-dependent atrial fibrillation, DTNPV1 was associated with a 1.50-fold (95% CI 1.06–2.13) increased risk of stroke. When added to the CHA2DS2-VASc variables, DTNPV1 did not significantly improve stroke prediction as assessed by C-statistic. However, there was improvement in risk classification for participants who did not develop stroke. ConclusionDTNPV1 is significantly associated with higher risk of ischemic stroke. Since DTNPV1 is a simplified electrocardiographic parameter, it may help stroke prediction, a subject for further research.

Atrial Fibrillation and Clonal Hematopoiesis in TET2 and ASXL1

Clonal hematopoiesis of indeterminate potential (CHIP) may contribute to the risk of atrial fibrillation (AF) through its association with inflammation and cardiac remodeling. To determine whether CHIP was associated with AF, inflammatory and cardiac biomarkers, and cardiac structural changes. This was a population-based, prospective cohort study in participants of the Atherosclerosis Risk in Communities (ARIC) study and UK Biobank (UKB) cohort. Samples were collected and echocardiography was performed from 2011 to 2013 in the ARIC cohort, and samples were collected from 2006 to 2010 in the UKB cohort. Included in this study were adults without hematologic malignancies, mitral valve stenosis, or previous mitral valve procedure from both the ARIC and UKB cohorts; additionally, participants without hypertrophic cardiomyopathy and congenital heart disease from the UKB cohort were also included. Data analysis was completed in 2023. CHIP (variant allele frequency [VAF] ≥2%), common gene-specific CHIP subtypes (DNMT3A, TET2, ASXL1), large CHIP (VAF ≥10%), inflammatory and cardiac biomarkers (high-sensitivity C-reactive protein, interleukin 6 [IL-6], IL-18, high-sensitivity troponin T [hs-TnT] and hs-TnI, N-terminal pro-B-type natriuretic peptide), and echocardiographic indices. Incident AF. A total of 199 982 adults were included in this study. In ARIC participants (4131 [2.1%]; mean [SD] age, 76 [5] years; 2449 female [59%]; 1682 male [41%]; 935 Black [23%] and 3196 White [77%]), 1019 had any CHIP (24.7%), and 478 had large CHIP (11.6%). In UKB participants (195 851 [97.9%]; mean [SD] age, 56 [8] years; 108 370 female [55%]; 87 481 male [45%]; 3154 Black [2%], 183 747 White [94%], and 7971 other race [4%]), 11 328 had any CHIP (5.8%), and 5189 had large CHIP (2.6%). ARIC participants were followed up for a median (IQR) period of 7.0 (5.3-7.7) years, and UKB participants were followed up for a median (IQR) period of 12.2 (11.3-13.0) years. Meta-analyzed hazard ratios for AF were 1.12 (95% CI, 1.01-1.25; P = .04) for participants with vs without large CHIP, 1.29 (95% CI, 1.05-1.59; P = .02) for those with vs without large TET2 CHIP (seen in 1340 of 197 209 [0.67%]), and 1.45 (95% CI, 1.02-2.07; P = .04) for those with vs without large ASXL1 CHIP (seen in 314 of 197 209 [0.16%]). Large TET2 CHIP was associated with higher IL-6 levels. Additionally, large ASXL1 was associated with higher hs-TnT level and increased left ventricular mass index. Large TET2 and ASXL1, but not DNMT3A, CHIP was associated with higher IL-6 level, indices of cardiac remodeling, and increased risk for AF. Future research is needed to elaborate on the mechanisms driving the associations and to investigate potential interventions to reduce the risk.

Self-Rated Health in Middle Age and Risk of Hospitalizations and Death: Recurrent Event Analysis of the ARIC Study.

Self-rated health is a simple measure that may identify individuals who are at a higher risk for hospitalization or death. To quantify the association between a single measure of self-rated health and future risk of recurrent hospitalizations or death. Atherosclerosis Risk in Communities (ARIC) study, a community-based prospective cohort study of middle-aged men and women with follow-up beginning from 1987 to 1989. We quantified the associations between initial self-rated health with risk of recurrent hospitalizations and of death using a recurrent events survival model that allowed for dependency between the rates of hospitalization and hazards of death, adjusted for demographic and clinical factors. Of the 14,937 ARIC cohort individuals with available self-rated health and covariate information, 34% of individuals reported "excellent" health, 47% "good," 16% "fair," and 3% "poor" at study baseline. After a median follow-up of 27.7years, 1955 (39%), 3569 (51%), 1626 (67%), and 402 (83%) individuals with "excellent," "good," "fair," and "poor" health, respectively, had died. After adjusting for demographic factors and medical history, a less favorable self-rated health status was associated with increased rates of hospitalization and death. As compared to those reporting "excellent" health, adults with "good," "fair," and "poor" health had 1.22 (1.07 to 1.40), 2.01 (1.63 to 2.47), and 3.13 (2.39 to 4.09) times the rate of hospitalizations, respectively. The hazards of death also increased with worsening categories of self-rated health, with "good," "fair," and "poor" health individuals experiencing 1.30 (1.12 to 1.51), 2.15 (1.71 to 2.69), and 3.40 (2.54 to 4.56) times the hazard of death compared to "excellent," respectively. Even after adjusting for demographic and clinical factors, having a less favorable response on a single measure of self-rated health taken in middle age is a potent marker of future hospitalizations and death.

APOL1 Kidney Risk Variants and Long-Term Kidney Function in Healthy Middle-Aged Black Individuals: The Atherosclerosis Risk in Communities (ARIC) Study

Rationale and ObjectiveImpact of Apolipoprotein L1(APOL1) genotype on future risk of kidney disease among middle-aged individuals with good kidney function is not well established. Study DesignLongitudinal cohort study. Setting & Participants5,886 healthy individuals, 45-64 years old, enrolled in the Atherosclerosis Risk in Communities study with eGFRcr ≥ 80 mL/min who would be suitable kidney donors. ExposuresRace and APOL1 genotype OutcomesEGFRcr-cys using CKD-EPI 2021 equation, uACR, proportion with CKD 3a or worse, ESKD and death. Analytical ApproachParticipants grouped on race and APOL1 genotype. Compared eGFRcr-cys and uACR across groups. Multinomial logistic regression models were used compare odds of CKD. Kaplan-Meier survival curves were created to compare rates of ESKD and death at last follow-up. ResultsThere were 5,075 whites (86%), 701 Blacks carrying low-risk APOL1 genotype (12%) and 110 Blacks carrying high-risk APOL1 genotype (2%). The mean age at baseline was 53±6 years. At 10 years, white participants had lower eGFRcr-cys than low-risk and high-risk groups (89±16 vs. 91±16 and 92±15 mL/min/1.73m2, respectively; p <0.001). At 25 years, white participants continued to have lower eGFRcr-cys than low-risk group (70±18 vs. 72±19 mL/min/1.73m2; p <0.001) but not compared to high risk APOL1 genotype (67±23 mL/min/1.7m2). There was no difference in uACR among groups at 10 and 25 years (p=0.87 and 0.91 respectively). The odds of developing CKD Stage 3a or worse were not different between low-risk and high-risk APOL1 group in both unadjusted and adjusted models (p=0.26 and p=0.39, respectively). At last follow-up, < 5% developed ESKD and 45% of individuals either died or reached ESKD with no difference in outcomes between the groups. LimitationsLow ascertainment due to death and long follow-up ConclusionsAmong middle-aged individuals, APOL1 genotype does not appear to be a major driver of future risk of kidney disease.

Social relationships, amyloid burden, and dementia: The ARIC-PET study.

This study aimed to assess whether social relationships in mid-life reduce the risk of dementia related to amyloid burden. Participants in the Atherosclerosis Risk in Communities (ARIC) study were assessed for social support and isolation (visit 2; 1990-1992). A composite measure, "social relationships," was generated. Brain amyloid was evaluated with florbetapir positron emission tomography (PET); (visit 5; 2012-2014). Incident dementia cases were identified following visit 5 through 2019 using ongoing surveillance. Relative contributions of mid-life social relationships and elevated brain amyloid to incident dementia were evaluated with Cox regression models. Among 310 participants without dementia, strong mid-life social relationships were associated independently with lower dementia risk. Elevated late-life brain amyloid was associated with greater dementia risk. Although mid-life social relationships did not moderate the relationship between amyloid burden and dementia, these findings affirm the importance of strong social relationships as a potentially protective factor against dementia.

Abstract 4772: Metabolic phenotype, age acceleration, and obesity-related cancer risk in Women's Health Initiative and Atherosclerosis Risk in Communities cohorts

Abstract Introduction: While normal physiologic aging causes metabolic decline, metabolic dysregulation owing to excess nutrient intake, physical inactivity, and obesity may drive accelerated aging. However, the relationship of accelerated aging with metabolic dysfunction across different levels of BMI (i.e., metabolic obesity phenotype) and whether it may mediate the relationship with obesity-related cancer (ORC) risk is not well established. Methods: To test this hypothesis, we are leveraging existing blood-based DNA methylation (DNAm) data within the Women’s Health Initiative (WHI) and the Atherosclerosis Risk in Communities (ARIC) cohorts. Weight, height and blood pressure were measured by trained technicians in the respective cohorts and fasting blood glucose, triglycerides and HDL cholesterol were quatified by standard clinican assays. Metabolic obesity phenotypes are classified as metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight/obese (MHO), and metabolically unhealthy overweight/obese (MUO) when defined by ATP III criteria. Age acceleration was measured as a residual from regressing pan-tissue Horvath’s DNAmAge on chronological age. Results: The mean baseline age was 64 ± 6.6 years and 54 ± 5.7 year among WHI and ARIC participants, respectively and the age acceleration was measured at an mean follow-up time of 16 years from baseline for WHI and 3.5 years from baseline for ARIC cohort. The outcome of interest, ORC incidence was observed among 474 participants of which 387 were women. The median time for cancer diagnosis from baseline was 25 year and from DNAm measurement was 18.6 years. Of the 4341 (70% women) participants included in the analysis, 23.9% were MHNW, 3.2% MUNW, 39% MHO, and 33.5% MUO. A 31.5% of MHNW, 40.4% of MUNW, 28.7% of MHO, and 35.2% of MUO showed age acceleration. MUNW (OR 1.47, 95% CI: 1.03-2.11) and MUO (OR 1.18, 95% CI: 1.00-1.40) individuals at baseline had increased odds of experiencing age acceleration at a follow-up visit. The risk of all ORC combined was significantly elevated among MUO (HR 1.63, 95% CI: 1.27-2.09) compared to MHNW. Age acceleration at the follow-up visit was not significantly associated with ORC risk (HR 0.91, 95% CI: 0.75-1.11). These analyses were not adjusted for confounders. Conclusions: MUNW and MUO individuals had increased odds of age acceleration at a follow-up visit. Furthermore, MUO individuals were at an elevated risk of ORC, compared to individuals with MHNW. Accelerated aging does not appear to mediate this association, as accelerated aging was not associated with ORC. Citation Format: Prasoona Karra, Garnet L. Anderson, Mary C. Playdon, Sheetal Hardikar, Aladdin Shadyab, Kari E. North, Anne E. Justice, Elizabeth A. Platz, Jan Bressler, Anna Prizment, Weihua Guan, Dominique S. Michaud, Eric A. Whitsel, Brock C. Christensen, Lucas A. Salas. Metabolic phenotype, age acceleration, and obesity-related cancer risk in Women's Health Initiative and Atherosclerosis Risk in Communities cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4772.

Abstract 3452: Senescence-associated secretory phenotype (SASP) aging index is associated with cancer risk in the Atherosclerosis Risk in Communities (ARIC) Study

Abstract Background: The accumulation of senescent cells, which release SASP proteins damaging neighboring cells, contributes to aging and age-related diseases, such as cancer. Therefore, SASP proteins could be used as biomarkers for individuals’ aging process, but no studies have tested if SASP protein-based aging index is associated with cancer risk. We created a SASP-aging index based on the 72 SASP proteins reported in Tanaka et al. [2018] and examined its association with cancer risk in the ARIC study. Methods: ARIC is an ongoing cohort of White and Black females and males initiated in 1987, followed for cancer until 2015 (median follow-up=17.3 yrs). At Visit 2 (1990-92), 5000 plasma proteins were measured using SomaScan – an aptamer-based assay in 10,834 participants (aged 46-70 yrs, 55% female, 76% White): 3,347 participants developed cancer during follow-up and 7,487 participants stayed cancer-free. In the training set of 67% randomly selected cancer-free participants, we constructed the SASP-aging index by applying Ridge regression to train the 72 SASP proteins against chronological age. The SASP-aging index was validated in the remaining 33% of cancer-free participants (test set). We calculated age acceleration as residuals after regressing the SASP-aging index on age in participants after excluding the training set. We used Cox proportional hazards regression to estimate hazard ratio (HR) and 95% confidence intervals (CI) for the risk of any type of cancer per 5 years increase in age acceleration, employing Barlow’s method [1994] to account for the exclusion of the training set. HR was adjusted for age, sex, race, center, education, BMI, smoking status, alcohol intake, aspirin use, diabetes, and eGFR. We also estimated HRs for obesity-related, smoking-related, and the most common cancers (breast, prostate, colorectal, and lung). Results: In the test set, Pearson correlation coefficient between the SASP-aging index and age was 0.50. Age acceleration was significantly associated with the risk of any type of cancer [HR (95% CI) per 5 years=1.21 (1.08-1.36)]. There was a suggestion of a higher HR for any type of cancer in females [1.26 (1.07-1.48)] than males [1.18 (1.00-1.39)] [p-interaction=0.08], but HRs were similar across race and smoking status [p-interaction&amp;gt;0.50]. Age acceleration was significantly associated with the risk of obesity-related cancers [1.36 (1.20-1.54)]. A significant association was also found with smoking-related cancers [1.43 (1.24-1.65)] and this association remained significant even among never smokers [1.39 (1.07- 1.82)]. Age acceleration was also significantly associated with colorectal [1.34 (1.03-1.75)] and lung cancer risk [1.63 (1.31-2.02)] but not with breast or prostate cancer risk. Conclusion: SASP protein-based aging index shows promise as a potential biomarker for cancer risk. Funding: NHLBI, NCI, NPCR Citation Format: Shuo Wang, Zexi Rao, Anne H. Blaes, Josef Coresh, Corinne E. Joshu, James S. Pankow, Bharat Thyagarajan, Peter Ganz, Elizabeth A. Platz, Weihua Guan, Anna Prizment. Senescence-associated secretory phenotype (SASP) aging index is associated with cancer risk in the Atherosclerosis Risk in Communities (ARIC) Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3452.

Abstract 6084: Identification of plasma proteins for early detection of cancer, including lung, in the Atherosclerosis Risk in Communities (ARIC) study

Abstract Background: Plasma proteins, directly secreted from tumor cells or a result of the body’s response to a tumor, may have utility for early detection. We aimed to identify plasma protein combinations that predict prediagnostic cancers in a prospective study. Methods: We sampled from 8,186 ARIC study participants without a cancer diagnosis at blood draw and with 4,877 log2-transformed proteins measured by SomaScan. We selected as cases those diagnosed within 5 years after blood draw and were registry/medical record confirmed. We selected as controls those who never had a cancer history by 2015 and did not die of cancer. Participants with possible liver, kidney, or inflammatory conditions were excluded (eGFR-cr&amp;lt;30, top 1% of plasma AST, ALT, CRP). Highly correlated proteins (r&amp;gt;±0.75), abundant or known markers (albumin, CRP, PSA), and proteins with wide log2-transformed distributions (SD&amp;gt;1 and &amp;gt;10% outliers-1.5 IQR away from 25th or 75th percentile) among controls were excluded. Recursive feature elimination (RFE) with random forest (RF) was used to select the top 10 informative proteins based on accuracy. Non-protein features included demographic, lifestyle (e.g., smoking), and medical factors. We next divided participants into train and test sets in 7:3 ratio stratified by case status. RF including top 10 proteins from the RFE and non-protein features trained in the train set were used to predict near-term cancer status in the test set and to calculate prediction performance. Random Over-Sampling Examples were used to balance between rare cases (&amp;lt;3%) and controls in the dataset. Results: We included 210 cases (98 diagnosed within 2 years) and 7,042 controls with 3,476 proteins. 58% were female, 24% were Black, and median age was 57 years (IQR: 52-62). The most common cancer was lung (27%). In the test set, sensitivity and specificity of the model for total cases diagnosed within 2 years were 0.19 and 0.91. Results for cases diagnosed within 3 (0.24, 0.88) and 5 (0.29, 0.87) years were similar. Using the top 10 informative proteins for total cancer, sensitivity was 0.68 and specificity was 0.56 for lung cancers diagnosed within 2 years; for lung cancers diagnosed within 3 (0.55, 0.77) or 5 (0.53, 0.79) years, sensitivity decreased but specificity increased. Using the top 10 informative proteins specific for lung cancer, which did not overlap with the top 10 for total cancer, sensitivity and specificity were 0.69 and 0.67 for lung cancers diagnosed within 2 years. Conclusions: In this study, in which blood draw preceded diagnosis, top informative proteins did not provide sufficient sensitivity for all-cancer near-term prediction. For lung cancer, further optimization may improve the sensitivity and specificity to achieve the range required for population implementation for screening. Validation with more cases, and on other proteomic platforms are needed. Funding NHLBI, NCI, NPCR Citation Format: Meng Ru, Christopher Douville, Kenneth R. Butler, Corinne E. Joshu, Jiayun Lu, Anna Prizment, Josef Coresh, Elizabeth A. Platz. Identification of plasma proteins for early detection of cancer, including lung, in the Atherosclerosis Risk in Communities (ARIC) study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6084.

Abstract 844: DNA methylation-derived immune cell profiles and risk of cancers in Black participants in the ARIC Study

Abstract Background: Prior cohort studies assessing cancer risk based on immune cell subtype profiles have predominantly focused on White populations. This limitation can obscure vital insights into how cancer risks vary across races, ethnicities, or exposures. This study was designed with the purpose of examining associations between pre-diagnostic immune cell profiles and cancer risk in Black participants. Methods: In this study, DNA methylation was measured in blood samples collected between 1993 and 1995 from a subset of 2,467 Black participants in the Atherosclerosis Risk in Communities (ARIC) prospective cohort study. Immune cell subtype proportions were estimated using deconvolution based on leukocyte DNA methylation markers. The analysis included 668 incident cancers ascertained between time of blood draw and 2015. Cox proportional hazards regression models were used to analyze the association between immune cell subtype proportions and cancer incidence (all cancers; lung, breast, and prostate cancers). Models controlled for age, sex, BMI, self-reported smoking status, self-reported and methylation-derived smoking pack-years, postmenopausal hormone use, and batch effect, along with other cancer-specific factors. Results: Increased T regulatory cell (Treg) proportions were associated with significantly higher risk of lung cancer (HR: 1.22, 95% CI = 1.06, 1.41 per percent increase; n = 84 cases) and suggestively higher risk of all cancers. Increased B memory cell proportions were associated with significantly higher risk of prostate cancer (HR: 1.17, 95% CI = 1.04, 1.33; n = 173 cases), all cancers (HR: 1.13, 95% CI = 1.05, 1.22), and suggestively higher risk of lung cancer. Increased CD8+ naïve cell proportions were associated with suggestively lower risk of lung cancer and all cancers, and significantly lower risk of all cancers in participants over the median age of 55 years (HR: 0.91, 95% CI = 0.83, 0.98). Cancer risks for other immune cell subtypes were null. Conclusions: These results in Black participants align closely with prior findings in largely White populations. Deconvolution allowed for the extension of work on cancer immunity (which has largely focused on major immune cell types) to immune cell subtypes like B memory cells and CD8+ naïve cells. The results are consistent with Tregs initiating and accelerating cancer development by impeding the usual protective immune response. A large reservoir of CD8+ naïve cells may allow for a more targeted and efficient elimination of malignant clones. Further studies should assess these relationships in other cancer types and better elucidate the interplay of B cells in theorized mechanistic processes. This study provides insight into the role of immune cell subtypes in cancer risk among Black men and women. Funding: NHLBI, NCR, NPCR Citation Format: Christopher S. Semancik, Naisi Zhao, Devin Koestler, Eric Boerwinkle, Jan Bressler, Karl Kelsey, Elizabeth A. Platz, Dominique S. Michaud. DNA methylation-derived immune cell profiles and risk of cancers in Black participants in the ARIC Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 844.

Abstract 4443: Trans-population two-sample Mendelian randomization study of circulating metabolites and prostate cancer risk

Abstract While prostate cancer (PCa) is highly heritable, mechanisms underlying disease risk and PCa disparities are not well understood. Here, we conducted a two-sample Mendelian randomization (MR) to assess whether serum metabolites are causally associated with PCa risk in European, African, and Hispanic populations. MR analyses were performed on metabolite quantitative trait loci (mQTLs) for 250 metabolites quantified by untargeted mass spectroscopy via the Metabolon platform for 1,498 European and 1,740 African ancestry individuals from the Atherosclerosis Risk in Communities (ARIC) cohort and for 711 metabolites measured in 3,166 Hispanic individuals from the Hispanic Community Health Study/Study of Latinos (SOL). PCa GWAS summary statistics were obtained for men from European (122,188 cases, 604,640 controls), African (19,391 cases, 61,608 controls) and Hispanic (3,931 cases, 26,405 controls) populations from the PRACTICAL Consortium. Within each population, QTLs associated with metabolites at the genome-wide significance level (P&amp;lt;5x10-8) were included in instruments upon removing rare (minor allele frequency≤0.01) or correlated (R2≥0.2) SNPs calculated in ancestry-matched TOPMed populations. Inverse variance weighted (IVW) random effect models are presented as primary results. Sensitivity analyses were utilized to assess assumption violations (weighted mode, weighted median and MR egger). MR were conducted separately in each population, and fixed effect meta-analyses were conducted across population-specific MR results to identify trans-population associations. A false discovery rate was implemented to account for multiple testing. In total, 22, 4 and 1 metabolites significantly associated with PCa risk in Hispanic, European and African populations, respectively. Of these, 13 metabolites had a MR instrument in ≥1 population, 12 of which were significant following a trans-population meta-analysis, including 5 fatty acids, 3 lysophospholipids, 1 amino acid, 1 carbohydrate, 1 nucleotide and 1 xenobiotic. All fatty acids were associated with decreased PCa odds (2%-10%), as were 4 other metabolites (amino acid 3-methyoxytyrosine, nucleotide 5-methyluridine and lysophospholipids 1-archidonoyl-GPC (20:4n6) and 1-archidonoyl-GPE (20:4n6), 4%-9%). The 3 remaining metabolites, erythritol, 1-linoleoyl-GPE (18:2) and mannose, were found to increase PCa odds by 10%, 6% and 4%, respectively. Additional metabolite harmonization efforts are underway to conduct trans-population analyses metabolome-wide. This study provides evidence of associations between metabolites, such as fatty acids and lysophysopholipids, and PCa across diverse populations. These findings point to mechanisms that could inform preventive or therapeutic strategies pending functional investigations. Multivariable and bidirectional MR are ongoing to further assess findings. Citation Format: Harriett Fuller, Rebecca Rohde, Heather Highland, Jiayi Shen, Bing Yu, Eric Boerwinkle, Megan Grove, Kari E. North, David V. Conti, Christopher A. Haiman, Kristin Young, Burcu Darst. Trans-population two-sample Mendelian randomization study of circulating metabolites and prostate cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4443.

Abstract MP33: Investigating the Link Between Glucose Patterns Assessed by Continuous Glucose Monitoring With Cognitive Impairment in Older Adults With Diabetes

Introduction: There are no studies in older adults with type 2 diabetes that examine the link between day-to-day glucose patterns and cognitive dysfunction. Continuous glucose monitoring (CGM) is a minimally invasive technology that can assess glucose every 1-15 minutes and characterize nuanced patterns in glucose. Hypothesis: CGM can provide a comprehensive picture of glycemic variability in people with cognitive dysfunction. Methods: We conducted a cross-sectional study of participants with diabetes in the Atherosclerosis Risk in Communities (ARIC) Study (Visit 9, 2021-2022). ARIC participants wore a CGM (Abbott Libre Pro) and underwent cognitive testing in three cognitive domains (memory, executive functioning, and language). Scores were standardized and averaged to give a global cognitive z-score. We compared HbA1c and clinically used CGM parameters (mean glucose, coefficient of variation, percent time in glucose range of 70-180 mg/dL, and percent time above 180 mg/dL) across quartiles of cognitive z-scores, adjusting for age and sex. We calculated p-values for trends from linear or quantile regression treating the median of cognitive Z-score in each quartile as a continuous variable. Results: We included 383 participants with diabetes (mean age, 83 years). Across categories of cognitive functioning, participants in the lowest cognitive functioning categories had significantly higher HbA1c, glucose variability, and less percent time spent with glucose in range (70-180 mg/dl) (Figure) . There was no clear trend in CGM mean glucose (p=0.15) (Figure, Panel B) . Conclusions: Cognitive dysfunction was associated with an increased burden of glycemic dysregulation assessed through CGM and HbA1c. Our results suggest CGM may be a useful complement to HbA1c for monitoring glycemic control in this population. Figure: Hemoglobin A1c (HbA1c) and continuous glucose monitoring (CGM) metrics across quartiles of cognitive Z-scores in older participants with diabetes in the ARIC Study (2021-2022)

Abstract P245: Association Between Individual Socioeconomic Status and Discharge Dispositions to Home or Rehabilitation Following Incident Stroke Hospitalization: The Atherosclerosis Risk in Communities (ARIC) Study

Background: The contribution of socioeconomic status (SES) to discharge destination in stroke survivors is not known. Hypothesis: Discharge to home, as compared to inpatient rehabilitation, will be greater among stroke survivors with low, as compared to high SES. Methods: The study population included ARIC Study participants, enrolled in fee-for-service Medicare, aged 66 years or older, with incident ischemic or hemorrhagic stroke (1992-2017). Black participants from the Minneapolis and Washington County study centers were excluded due to low numbers. Individual SES was estimated from median household income and education. Discharge disposition was ascertained from CMS Medicare inpatient records. Logistic regression models with inverse probability of treatment weighting were used to estimate the effect of exposures, accounting for age, sex, race, study center, comorbidity, and stroke severity. The Elixhauser Comorbidity Index was used to as a measure of comorbidity burden. Stroke severity was estimated from discharge diagnosis and procedure codes obtained from Medicare hospitalization records. Results: Of a total 710 ARIC stroke survivors (mean age at discharge 76 (SD: 6.2) years, 30.1% (214 of 710) Black, 57.5% (408 of 710) women), 50.7% (360 of 710) were discharged home. Compared to high income, low and moderate income was associated with lower adjusted odds of discharge to home among White participants (AOR:0.8, 95% CI: 0.68-0.93) and AOR: 0.63, 95% CI: 0.57-0.69), respectively) and higher odds discharge to home among Black participants (AOR: 1.36, 95% CI: 1.07-1.73 and AOR: 1.43, 95% CI: 1.11-1.83, respectively). Low income was also associated with higher odds of discharge home among women. Adjustment for stroke severity and comorbidity did not attenuate estimates. No significant association between education and discharge disposition was observed. Conclusions: Low and moderate median household income is statistically significantly associated with discharge home among Black and female stroke survivors.

Abstract P134: Bidirectional Association of Diabetes and Heart Failure

Background: Diabetes and heart failure (HF) frequently coexist. Diabetes is a major risk factor for HF, but physiological studies have also shown that HF promotes insulin resistance, and thus may predispose to diabetes. However, the bidirectional association between diabetes and HF has seldom been examined in community-based studies. Methods: We conducted a prospective analysis of 10982 individuals (mean age 63.3 years, 56% women, ~22% Black adults, 1822 [16.6%] with prevalent diabetes and 606 [5.5%] with prevalent HF) who attended Visit 4 (1996-1998) of the Atherosclerosis Risk in Communities (ARIC) Study. We used Cox regression to examine the association of prevalent HF at Visit 4 or incident HF after Visit 4 with the incidence of diabetes, as well as the association of prevalent diabetes at Visit 4 or incident diabetes after Visit 4 with the incidence of HF. We also assessed individual and joint associations of diabetes and HF at Visit 4 with mortality. Results: Of the 606 individuals with prevalent HF by Visit 4, more than half (52.3%) had or developed diabetes. Among 1822 individuals with prevalent diabetes at Visit 4, 44% had a history of HF. Prevalent HF (hazard ratio [HR]: 1.34, 95%CI: 1.09, 1.64; no HF as referent) and incident HF (HR: 1.32, 95%CI: 1.08, 1.61) were each associated with incident diabetes. Prevalent diabetes (HR, 1.83; 95% CI, 1.64, 2.03; no diabetes as referent) and incident diabetes (HR: 1.37, 95%CI: 1.21, 1.56) were each associated with incident HF. The presence of both prevalent HF and diabetes conferred greater overall mortality (HR: 2.59, 95% CI: 2.22, 3.02) and cardiovascular mortality (HR: 3.82, 95% CI: 3.06, 4.78) risks compared with the absence of both conditions or either condition alone. Conclusions: Diabetes precedes and follows HF, with each condition being a risk factor for the other. The coexistence of both diabetes and HF is associated with a markedly elevated risk of mortality.

Abstract P511: Trajectories of Modifiable Risk Factors, Cardiac Function and Incident Heart Failure in the Atherosclerosis Risk in Communities (ARIC) Cohort

Introduction: Modifiable risk factors are known to associate with incident heart failure (HF), however, their longitudinal impacts have not been fully understood. Independent trajectory clusters of risk factors can help provide insights to the development of HF. Hypothesis: We hypothesize that unfavorable trajectory clusters are associated with increasing risk of HF. Methods: Clinical risk factors, including body mass index (BMI), systolic blood pressure (SBP), low-density lipoprotein (LDL), heart rate, total cholesterol (TCH), and high-density lipoprotein (HDL) were measured in Atherosclerosis Risk in Communities (ARIC) study at 5 consecutive visits (1987-2013). Trajectories were built for each clinical risk factor in participants with at least 3 time points using group-based trajectory modeling approach. Controlling for clinical risk factors, trajectory groups and their associations with post visit 5 incident HF were assessed via Cox proportional regression. Sex stratified analyses were conducted to assess effect modification. Results: Among 4,548 participants (mean age 75, 18.1% Blacks), 390 developed HF after visit 5 (median follow = 8.4 years). Five distinct clusters were identified for SBP, LDL, TCH, heart rate, and three clusters for BMI and HDL. Compared to the lowest cluster, normal-fast rising SBP cluster (HR = 1.7, 95% CI 1.2, 2.5), severely obese BMI cluster (HR = 1.9, 95%CI 1.4, 2.6), and normal-fast rising heart rate cluster (HR = 1.7, 95%CI 1.1, 2.5) had higher risk of developing HF. Interestingly, suboptimal-stable LDL cluster (HR = 0.6, 95%CI 0.4, 0.8) was associated with lower risk of HF compared to the optimal-stable LDL cluster. When stratified by sex (female =59.1%, male = 40.9%), the identified trajectories shared similar patterns with the parent trajectories. The effects on HF were consistent between sex groups; however, most significant associations were diminished in males. Conclusion: We identified distinct trajectories that capture long-term effects of risk factors. Unfavorable clusters significantly associated with increased risk of HF, except LDL, suggesting further investigation on lipids control for HF prevention.

Abstract P540: Sleep Duration, Rapid Eye Movement Sleep, and Subclinical Myocardial Damage

Introduction: Sleep is strongly linked to clinical cardiovascular disease and was added in 2022 to the AHA’s Life’s Essential 8. Optimizing sleep duration and quality may reduce the risk of cardiovascular disease. Few studies have examined self-reported sleep duration and percent time in rapid eye movement (REM) sleep measured by single night in-home polysomnography with high sensitivity cardiac troponin T (hs-troponin T), a biomarker of subclinical cardiovascular disease. Methods: We conducted a cross-sectional study of adults without a history of cardiovascular disease who participated in both the Atherosclerosis Risk in Communities (ARIC) Study and the Sleep Heart Health Study (SHHS) in 1995-1998. We used linear regression with sleep duration and percentage time of REM sleep modeled as predictors with restricted cubic splines and examined associations with the outcome, hs-troponin T. We adjusted for age, sex, body mass index, waist-to-hip ratio, alcohol intake, smoking status, systolic blood pressure, hypertension medication use, diabetes, HDL- and LDL-cholesterol, and cholesterol-lowering medication use. Results: Among 1,587 participants (mean age 63, 54% female), the mean sleep duration was 7.3 hours, and mean % REM time was 20.7. Sleep duration was not associated with hs-troponin T ( Figure, Panel A ). However, percentage REM sleep was negatively associated with hs-troponin T, but with a threshold effect; there was a negative linear association of hs-troponin T with % REM sleep but only at values &lt;15% ( Figure, Panel B ). Conclusion: While self-reported sleep duration was not associated with TnT levels, there was evidence that low % REM sleep, a specific neurophysiological sleep state, was associated with subclinical cardiovascular disease. These findings suggest that multiple sleep dimensions should be considered in efforts to optimize cardiovascular health.