Publications

Despite the availability of effective vaccines and a recent decrease in annual deaths, COVID-19 remains a leading cause of death. Serological studies provide insights into host immunobiology of adaptive immune response to infection, which holds promise for identifying high-risk individuals for adverse COVID-19 outcomes. We investigated correlates of anti-nucleocapsid antibody responses following SARS-CoV-2 infection in a US population-based meta-cohort of adults participating in longstanding National Institutes of Health-funded cohort studies. Anti-nucleocapsid antibodies were measured from dried blood spots collected between February 2021 and February 2023. Among 1419 Collaborative Cohort of Cohorts for COVID-19 Research participants with prior SARS-CoV-2 infection, the mean age (standard deviation) was 65.8 (12.1), 61% were women, and 42.8% self-reported membership in a race/ethnicity minority group. The proportion of participants reactive to nucleocapsid peaked at 69% by 4 months after infection and waned to only 44% ≥12 months after infection. Higher anti-nucleocapsid antibody response was associated with older age, Hispanic or American Indian Alaskan Native (vs White) race/ethnicity, lower income, lower education, former smoking, and higher anti-spike antibody levels. Asian race (vs White) and vaccination (even after infection) were associated with lower nucleocapsid reactivity. Neither vaccine manufacturer nor common cardiometabolic comorbidities were not associated with anti-nucleocapsid response. These findings inform the underlying immunobiology of adaptive immune response to infection, as well as the potential utility of anti-nucleocapsid antibody response for clinical practice and COVID-19 serosurveillance.

BACKGROUND: Cigarette smoking is a strong risk factor for cardiovascular harm.

OBJECTIVES: The study sought to explore the detailed relationships between smoking intensity, pack-years, and time since cessation with inflammation, thrombosis, and subclinical atherosclerosis markers of cardiovascular harm.

METHODS: We included 182,364 participants (mean age 58.2 years, 69.0% female) from 22 cohorts of the Cross Cohort Collaboration with self-reported smoking status, including smoking intensity and/or pack-years, and concurrent subclinical marker measurements. Markers were categorized into 3 domains: inflammation (high-sensitivity C-reactive protein, interleukin-6, glycoprotein acetylation), thrombosis (fibrinogen, D-dimer), and subclinical atherosclerosis (coronary artery calcium, carotid intima-media thickness, carotid plaque, and ankle-brachial index). Utilizing multivariate regression models and restricted cubic splines, we assessed associations of smoking status, intensity, pack-years, time since cessation, and subclinical markers.

RESULTS: A total of 15.3% of participants currently smoke (mean 16.7 cigarettes/day, mean 30.0 pack-years), and 34.6% of participants formerly smoked (median 19.0 years since quitting, mean 22.4 pack-years). Participants with a history of smoking showed higher levels of all subclinical markers compared with those who have never smoked, with stronger associations observed in those currently smoke. Among participants who currently smoke, smoking intensity showed a clear dose-response relationship with all markers, except for D-dimer, specifically with incremental 1% to 9% higher levels of subclinical markers per 10 cigarettes. After 20 cigarettes, the patterns appeared to plateau for blood markers, while they continued to increase for atherosclerosis markers. Among those who have ever smoked, robust dose-response relationships were observed for pack-years with all subclinical markers, with incremental 1% to 9% higher levels per 10 pack-years. The dose-response effects persisted after 20 pack-years for all markers, though with a milder slope. Among participants who smoked formerly, there were substantially lower levels of biomarkers with longer time since quitting, and most markers were not different compared with those who have never smoked by 30 years, except for the coronary artery calcium score, which remained 19% higher even beyond quitting after 30 years.

CONCLUSIONS: Smoking-relevant parameters show strong and dose-response relationships across 3 domains of subclinical markers of cardiovascular harm. The sensitivity of the tested subclinical markers to small increments in cigarette exposure suggests potential value in the regulation of new and existing tobacco products.

IMPORTANCE: Numerous efforts have been made to include diverse populations in genetic studies, but American Indian populations are still severely underrepresented. Polygenic scores derived from genetic data have been proposed in clinical care, but how polygenic scores perform in American Indian individuals and whether they can predict disease risk in this population remains unknown.

OBJECTIVE: To study the performance of polygenic scores for cardiometabolic risk factors of lipid traits and C-reactive protein in American Indian adults and to determine whether such scores are helpful in clinical prediction for cardiometabolic diseases.

DESIGN, SETTING, AND PARTICIPANTS: The Strong Heart Study (SHS) is a large American Indian cohort recruited from 1989 to 1991, with ongoing follow-up (phase VII). In this genetic association study, data from SHS American Indian participants were used in addition to data from 2 large-scale, external, ancestry-mismatched genome-wide association studies (GWASs; 450 865 individuals from a European GWAS and 33 096 individuals from a multi-ancestry GWAS) and 1 small-scale internal ancestry-matched American Indian GWAS (2000 individuals). Analyses were conducted from February 2023 to August 2024.

EXPOSURE: Genetic risk score for cardiometabolic disease risk factors from 6 traits including 5 lipids (apolipoprotein A, apolipoprotein B, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides), and an inflammatory biomarker (C-reactive protein [CRP]).

MAIN OUTCOMES AND MEASURES: Data from SHS participants and the 2 GWASs were used to construct 8 polygenic scores. The association of polygenic scores with cardiometabolic disease was assessed using 2-sided z tests and 1-sided likelihood ratio tests.

RESULTS: In the 3157 SHS participants (mean [SD] age, 56.44 [8.12] years; 1845 female [58.4%]), a large European-based polygenic score had the most robust performance (mean [SD] R2 = 5.0% [1.7%]), but adding a small-scale ancestry-matched GWAS using American Indian data helped improve polygenic score prediction for 5 of 6 traits (all but CRP; mean [SD] R2, 7.6% [3.2%]). Lipid polygenic scores developed in American Indian individuals improved prediction of diabetes compared with baseline clinical risk factors (area under the curve for absolute improvement, 0.86%; 95% CI, 0.78%-0.93%; likelihood ratio test P = 3.8 × 10-3).

CONCLUSIONS AND RELEVANCE: In this genetic association study of lipids and CRP among American Indian individuals, polygenic scores of lipid traits were found to improve prediction of diabetes when added to clinical risk factors, although the magnitude of improvement was small. The transferability of polygenic scores derived from other populations is still a concern, with implications for the advancement of precision medicine and the potential of perpetuating health disparities, particularly in this underrepresented population.

BACKGROUND: Understanding the association of tobacco product use with subclinical markers is essential in evaluating health effects to inform regulatory policy. This is particularly relevant for noncigarette products (eg, cigars, pipes, and smokeless tobacco), which have been understudied because of their low prevalence in individual cohort studies.

METHODS: This cross-sectional study included 98 450 participants from the Cross-Cohort Collaboration-Tobacco data set. Associations between the use of tobacco products and subclinical markers (high-sensitivity C-reactive protein, interleukin-6, fibrinogen, D-dimer, coronary artery calcium, carotid intima-media thickness, carotid plaque, and ankle-brachial index) were evaluated. The analyses used multivariable linear and logistic regression models to examine current use status for each product, with additional analyses of "sole" and "exclusive" noncigarette use (versus never use of either cigarettes or a specific noncigarette tobacco). Sole use was defined as the current use of a given noncigarette tobacco without concurrent combustible cigarette use, whereas exclusive use was defined as current noncigarette tobacco use without any history of combustible cigarette use.

RESULTS: A total of 20.0%, 3.0%, 0.8%, and 1.5% of participants were current cigarette, cigar, pipe, or smokeless tobacco users, respectively. Current cigarette use showed associations with higher levels of all markers compared with never cigarette use. Compared with the relevant reference group, current, sole, and exclusive cigar use was associated with 10% (95% CI, 1-20), 19% (95% CI, 12-26), and 11% (95% CI, 2-21) higher high-sensitivity C-reactive protein on the geometric mean scale. Similar associations were observed for pipe and smokeless tobacco use. For interleukin-6, we observed that sole cigar use was associated with a 15% (95% CI, 6-24) higher geometric mean level, whereas current, sole, and exclusive pipe use were associated with 22% to 32% (all P values <0.05) higher levels compared with their respective reference groups. Fibrinogen levels were 2% to 6% higher (all P values <0.05) among current users of cigars, pipes, and smokeless tobacco compared with their respective reference groups. Carotid plaque and carotid intima-media thickness were also moderately associated with noncigarette tobacco use.

CONCLUSIONS: Use of noncigarette tobacco products is linked to subclinical markers relevant to cardiovascular harm. Inflammatory markers, such as high-sensitivity C-reactive protein and interleukin-6, have the potential for assessing early cardiovascular risk from these products and aiding regulatory authorities in evaluating their associated risks.

INTRODUCTION: Compared with White Americans, American Indian adults have disproportionately high depression rates. Previous studies in non-American Indian populations report depression as common among people with uncontrolled hypertension, potentially interfering with blood pressure control. Few studies have examined the association of depressive symptoms with hypertension development among American Indians despite that population's high burden of depression and hypertension. We examined the association of depressive symptoms with incident hypertension in a large cohort of American Indians.

METHODS: We studied 1,408 American Indian participants in the Strong Heart Family Study, a longitudinal, ongoing, epidemiologic study assessing cardiovascular disease and its risk factors among American Indian populations. Depressive symptoms were assessed by using the Center for Epidemiological Studies-Depression (CES-D) scale, 2001-2003. At each study examination in 2001-2003 and 2007-2009, blood pressure was measured 3 times. The average of the last 2 measurements taken at baseline and follow-up examinations was used for analyses. Incident hypertension was defined as systolic blood pressure ≥140 mm Hg, diastolic blood pressure of ≥90 mm Hg, or use of hypertension medications at follow-up. To account for within-family correlation, we used generalized estimating equations to examine the association of depressive symptoms with incident hypertension.

RESULTS: During follow-up, 257 participants developed hypertension. Participants with symptoms consistent with depression (CES-D ≥16) at baseline had 54% higher odds of developing hypertension during follow-up (OR = 1.54; 95% CI, 1.06-2.23) compared with those without depression (CES-D <16) at baseline after adjustment for other risk factors.

CONCLUSION: These data suggest that participants who experienced symptoms consistent with depression were at increased odds of incident hypertension.

IMPORTANCE: Cardiovascular health outcomes associated with noncigarette tobacco products (cigar, pipe, and smokeless tobacco) remain unclear, yet such data are required for evidence-based regulation.

OBJECTIVE: To investigate the association of noncigarette tobacco products with cardiovascular health outcomes.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study was conducted within the Cross Cohort Collaboration Tobacco Working Group by harmonizing tobacco-related data and conducting a pooled analysis from 15 US-based prospective cohorts with data on the use of at least 1 noncigarette tobacco product ranging between 1948 and 2015. The analysis for this study was conducted between September 2023 and February 2024. The median (IQR) follow-up time for the all-cause mortality outcome was 13.8 (10.2-19.2) years.

EXPOSURE: Current, sole, and exclusive use of noncigarette tobacco products. Sole use refers to using a noncigarette tobacco product without currently smoking cigarettes. Exclusive use means using only the noncigarette tobacco product and never having smoked cigarettes.

MAIN OUTCOMES AND MEASURES: Myocardial infarction, stroke, heart failure, atrial fibrillation, total coronary heart disease, total cardiovascular disease (CVD), coronary heart disease mortality, CVD mortality, and all-cause mortality.

RESULTS: Of 103 642 participants (mean [SD] age, 55.7 [13.2] years; 49 550 female [47.8%] and 54 092 male [52.2%]), current use rates were 26 962 participants (26.3%) for cigarettes, 1147 participants (2.1%) for cigars, 530 participants (1.2%) for pipes, and 1410 participants (2.1%) for smokeless tobacco. Current cigar use was associated with stroke (hazard ratio [HR], 1.25; 95% CI, 1.01-1.55), atrial fibrillation (HR, 1.32; 95% CI, 1.13-1.53), and heart failure (HR, 1.29; 95% CI, 1.10-1.51) compared with never using cigars in the model adjusted for demographic and socioeconomic factors, cardiovascular risk factors, and cohort. Sole (HR, 1.34; 95% CI, 1.12-1.62) and exclusive (HR, 1.53; 95% CI, 1.20-1.96) cigar use was associated with stroke compared with never using cigars or cigarettes. Current pipe use was associated with heart failure (HR, 1.23; 95% CI, 1.01-1.49) compared with never using pipes, and sole pipe use was associated with myocardial infarction (HR, 1.43; 95% CI, 1.17-1.74) compared with never using pipes or cigarettes. Current use of smokeless tobacco was associated with coronary heart disease mortality (HR, 1.31; 95% CI, 1.08-1.59) and myocardial infarction (HR, 1.20; 95% CI, 1.03-1.39) compared with never using smokeless tobacco. Sole and exclusive smokeless tobacco use demonstrated associations with total CVD (HR, 1.34; 95% CI, 1.19-1.50 and HR, 1.34; 955 CI, 1.13-1.59, respectively), total coronary heart disease (HR, 1.41; 95% CI, 1.21-1.64 and HR, 1.36; 95% CI, 1.08-1.70, respectively), heart failure (HR, 1.41; 95% CI, 1.22-1.64 and HR, 1.70; 95% CI, 1.40-2.06, respectively), and cardiovascular (HR, 1.41; 95% CI, 1.20-1.65 and HR, 1.54; 95% CI, 1.24-1.91, respectively) and all-cause (HR, 1.46; 95% CI, 1.34-1.60 and HR, 1.39; 95% CI, 1.22-1.58, respectively) mortality compared with never using smokeless tobacco or cigarettes.

CONCLUSIONS AND RELEVANCE: In this study, there were distinct risk patterns associated with the use of noncigarette tobacco products. These findings may carry implications for public health and regulation of noncigarette tobacco products.

BACKGROUND: Uranium is a potentially cardiotoxic, nonessential element commonly found in drinking water throughout the United States.

OBJECTIVES: The purpose of this study was to evaluate if urinary uranium concentrations were associated with measures of cardiac geometry and function among American Indian young adults from the Strong Heart Family Study.

METHODS: Urinary uranium was measured among 1,332 participants free of diabetes, cardiovascular disease, and <50 years of age at baseline (2001-2003). Transthoracic echocardiography and blood pressure were assessed at baseline and at a follow-up visit (2006-2009). We estimated adjusted mean differences in cardiac geometry and function measures at baseline and follow-up using linear mixed-effect models with a random intercept and slope over time.

RESULTS: Median (interquartile range) uranium was 0.029 (0.045) μg/g creatinine. In fully adjusted cross-sectional models, a log-doubling of urinary uranium was positively associated with left ventricular (LV) mass index (mean difference: 0.49 g/m2, 95% CI: 0.07-0.92 g/m2), left atrial systolic diameter (0.01 cm/m2, 0.01-0.02 cm/m2), and stroke volume (0.66 mL, 0.25-1.08 mL) at baseline. Prospectively, uranium was associated with increases in left atrial diameter (0.01 cm/m2, 0.01-0.02 cm/m2), pulse pressure (0.28 mm Hg, 0.05-0.52 mm Hg), and incident LV hypertrophy (odds ratio: 1.25, 95% confidence interval: 1.06, 1.48).

CONCLUSIONS: Urinary uranium levels were adversely associated with measures of cardiac geometry and LV function among American Indian adults, including increases in pulse pressure and LV hypertrophy. These findings support the need to determine the potential long-term subclinical and clinical cardiovascular effects of chronic uranium exposure, and the need for future strategies to reduce exposure.

BACKGROUND: Emerging evidence reveals a complex relationship between cardiovascular disease (CVD) and cancer, which share common risk factors and biological pathways.

OBJECTIVES: The aim of this study was to evaluate common epigenetic signatures for CVD and cancer incidence in 3 ethnically diverse cohorts: Native Americans from the SHS (Strong Heart Study), European Americans from the FHS (Framingham Heart Study), and European Americans and African Americans from the ARIC (Atherosclerosis Risk In Communities) study.

METHODS: A 2-stage strategy was used that included first conducting untargeted epigenome-wide association studies for each cohort and then running targeted models in the union set of identified differentially methylated positions (DMPs). We also explored potential molecular pathways by conducting a bioinformatics analysis.

RESULTS: Common DMPs were identified across all populations. In a subsequent meta-analysis, 3 and 1 of those DMPs were statistically significant for CVD only and both cancer and CVD, respectively. No meta-analyzed DMPs were statistically significant for cancer only. The enrichment analysis pointed to interconnected biological pathways involved in cancer and CVD. In the DrugBank database, elements related to 1-carbon metabolism and cancer and CVD medications were identified as potential drugs for target gene products. In an additional analysis restricted to the 950 SHS participants who developed incident CVD, the C index for incident cancer increased from 0.618 (95% CI: 0.570-0.672) to 0.971 (95% CI: 0.963-0.978) when adjusting the models for the combined cancer and CVD DMPs identified in the other cohorts.

CONCLUSIONS: These results point to molecular pathways and potential treatments for precision prevention of CVD and cancer. Screening based on common epigenetic signatures of incident CVD and cancer may help identify patients with newly diagnosed CVD at increased cancer risk.

Left ventricular hypertrophy (LVH) and dyslipidemia are strong, independent predictors for cardiovascular disease, but their relationship is less well-studied. A longitudinal lipidomic profiling of left ventricular mass (LVM) and LVH is still lacking. Using LC-MS, we repeatedly measured 1,542 lipids from 1,755 unique American Indians attending two exams (mean 5-year apart). Cross-sectional associations of individual lipid species with LVM index (LVMI) were examined by generalized estimating equation (GEE), followed by replication in an independent bi-racial cohort (65% white, 35% black). Baseline plasma lipids associated with LVH risk beyond traditional risk factors were identified by Cox frailty model in American Indians. Longitudinal associations between changes in lipids and changes in LVMI were examined by GEE, adjusting for baseline lipids, baseline LVMI, and covariates. Multiple lipid species (e.g., glycerophospholipids, sphingomyelins, acylcarnitines) were significantly associated with LVMI or the risk of LVH in American Indians. Some lipids were confirmed in black and white individuals. Moreover, some LVH-related lipids were inversely associated with risk of coronary heart disease (CHD). Longitudinal changes in several lipid species (e.g., glycerophospholipids, sphingomyelins, cholesterol esters) were significantly associated with changes in LVMI. These findings provide insights into the role of lipid metabolism in LV remodeling and the risk of LVH or CHD.

Coronary heart disease (CHD) is one of the leading causes of mortality and morbidity in the United States. Accurate time-to-event CHD prediction models with high-dimensional DNA methylation and clinical features may assist with early prediction and intervention strategies. We developed a state-of-the-art deep learning autoencoder survival analysis model (AESurv) to effectively analyze high-dimensional blood DNA methylation features and traditional clinical risk factors by learning low-dimensional representation of participants for time-to-event CHD prediction. We demonstrated the utility of our model in two cohort studies: the Strong Heart Study cohort (SHS), a prospective cohort studying cardiovascular disease and its risk factors among American Indians adults; the Women's Health Initiative (WHI), a prospective cohort study including randomized clinical trials and observational study to improve postmenopausal women's health with one of the main focuses on cardiovascular disease. Our AESurv model effectively learned participant representations in low-dimensional latent space and achieved better model performance (concordance index-C index of 0.864 ± 0.009 and time-to-event mean area under the receiver operating characteristic curve-AUROC of 0.905 ± 0.009) than other survival analysis models (Cox proportional hazard, Cox proportional hazard deep neural network survival analysis, random survival forest, and gradient boosting survival analysis models) in the SHS. We further validated the AESurv model in WHI and also achieved the best model performance. The AESurv model can be used for accurate CHD prediction and assist health care professionals and patients to perform early intervention strategies. We suggest using AESurv model for future time-to-event CHD prediction based on DNA methylation features.