Publications

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.

BACKGROUND: American Indian (AI) communities are affected by uranium exposure from abandoned mines and naturally contaminated drinking water. Few studies have evaluated geographical differences across AI communities and the role of dietary exposures.

OBJECTIVE: We evaluated differences in urinary uranium levels by diet and geographical area among AI participants from the Northern Plains, the Southern Plains, and the Southwest enrolled in the Strong Heart Family Study (SHFS).

METHODS: We used food frequency questionnaires to determine dietary sources related to urinary uranium levels for 1,682 SHFS participants in 2001-2003. We calculated adjusted geometric mean ratios (GMRs) of urinary uranium for an interquartile range (IQR) increase in self-reported food group consumption accounting for family clustering and adjusting for sociodemographic variables and other food groups. We determined the percentage of variability in urinary uranium explained by diet.

RESULTS: Median (IQR) urinary uranium levels were 0.027 (0.012, 0.057) μg/g creatinine. Urinary uranium levels were higher in Arizona (median 0.039 μg/g) and North Dakota and South Dakota (median 0.038 μg/g) and lower in Oklahoma (median 0.019 μg/g). The adjusted percent increase (95% confidence interval) of urinary uranium levels per IQR increase in reported food intake was 20% (5%, 36%) for organ meat, 11% (1%, 23%) for cereals, and 14% (1%, 29%) for alcoholic drinks. In analyses stratified by study center, the association with organ meat was specific to North Dakota and South Dakota participants. An IQR increase in consumption of fries and chips was inversely associated with urinary uranium levels -11% (-19%, -3%). Overall, we estimated that self-reported dietary exposures explained 1.71% of variability in urine uranium levels.

IMPACT: Our paper provides a novel assessment of self-reported food intake and urinary uranium levels in a cohort of American Indian participants. We identify foods (organ meat, cereals, and alcohol) positively associated with urinary uranium levels, find that organ meat consumption is only associated with urine uranium in North Dakota and South Dakota, and estimate that diet explains relatively little variation in total urinary uranium concentrations. Our findings contribute meaningful data toward a more comprehensive estimation of uranium exposure among Native American communities and support the need for high-quality assessments of water and dust uranium exposures in SHFS communities.

The last couple of decades have highlighted the importance of studying hybridization, particularly among primate species, as it allows us to better understand our own evolutionary trajectory. Here, we report on genetic ancestry estimates using dense, full genome data from 881 olive (Papio anubus), yellow (Papio cynocephalus), or olive-yellow crossed captive baboons from the Southwest National Primate Research Center. We calculated global and local ancestry information, imputed low coverage genomes (n = 830) to improve marker quality, and updated the genetic resources of baboons available to assist future studies. We found evidence of historical admixture in some putatively purebred animals and identified errors within the Southwest National Primate Research Center pedigree. We also compared the outputs between two different phasing and imputation pipelines along with two different global ancestry estimation software. There was good agreement between the global ancestry estimation software, with R2 > 0.88, while evidence of phase switch errors increased depending on what phasing and imputation pipeline was used. We also generated updated genetic maps and created a concise set of ancestry informative markers (n = 1,747) to accurately obtain global ancestry estimates.

BACKGROUND: Chronic kidney disease (CKD) is highly prevalent in Central America, and genetic factors may contribute to CKD risk. To understand the influences of genetic admixture on CKD susceptibility, we conducted an admixture mapping screening of CKD traits and risk factors in US Hispanic and Latino individuals from Central America country of origin.

METHODS: We analyzed 1023 participants of HCHS/SOL (Hispanic Community Health Study/Study of Latinos) who reported 4 grandparents originating from the same Central America country. Ancestry admixture findings were validated on 8191 African Americans from WHI (Women's Health Initiative), 3141 American Indians from SHS (Strong Heart Study), and over 1.1 million European individuals from a multistudy meta-analysis.

RESULTS: We identified 3 novel genomic regions for albuminuria (chromosome 14q24.2), CKD (chromosome 6q25.3), and type 2 diabetes (chromosome 3q22.2). The 14q24.2 locus driven by a Native American ancestry had a protective effect on albuminuria and consisted of 2 nearby regions spanning the RGS6 gene. Variants at this locus were validated in American Indians. The 6q25.3 African ancestry-derived locus, encompassing the ARID1B gene, was associated with increased risk for CKD and replicated in African Americans through admixture mapping. The European ancestry type 2 diabetes locus at 3q22.2, encompassing the EPHB1 and KY genes, was validated in European individuals through variant association.

CONCLUSIONS: US Hispanic/Latino populations are culturally and genetically diverse. This study focusing on Central America grandparent country of origin provides new loci discovery and insights into the ancestry-of-origin influences on CKD and risk factors in US Hispanic and Latino individuals.

BACKGROUND: A growing body of research indicates that associations of ceramides and sphingomyelins with mortality depend on the chain length of the fatty acid acylated to the backbone sphingoid base. We examined associations of 8 ceramide and sphingomyelin species with mortality among an American Indian population.

METHODS AND RESULTS: The analysis comprised 2688 participants from the SHFS (Strong Heart Family Study). Plasma ceramide and sphingomyelin species carrying long-chain (ie, 16:0) and very-long-chain (ie, 20:0, 22:0, 24:0) saturated fatty acids were measured by sequential liquid chromatography and mass spectroscopy using samples from 2001 to 2003. Participants were followed for 18.8 years (2001-2020). Associations of ceramides and sphingomyelins with mortality were assessed using Cox models. The mean age of participants was 40.8 years. There were 574 deaths during a median 17.4-year follow-up. Ceramides and sphingomyelins carrying fatty acid 16:0 were positively associated with mortality. Ceramides and sphingomyelins carrying longer fatty acids were inversely associated with mortality. Per SD difference in each ceramide and sphingomyelin species, hazard ratios for death were: 1.68 (95% CI, 1.44-1.96) for ceramide-16 (Cer-16), 0.82 (95% CI, 0.71-0.95) for Cer-20, 0.60 (95% CI, 0.51-0.70) for Cer-22, 0.67 (95% CI, 0.56-0.79) for Cer-24, 1.80 (95% CI-1.57, 2.05) for sphingomyelin-16 (SM-16), 0.54 (95% CI, 0.47-0.62) for SM-20, 0.50 (95% CI, 0.44-0.57) for SM-22, and 0.59 (95% CI, 0.52-0.67) for SM-24.

CONCLUSIONS: The direction/magnitude of associations of ceramides and sphingomyelins with mortality differs according to the length of the fatty acid acylated to the backbone sphingoid base.

REGISTRATION: URL: https://www.clinicatrials.gov; Unique identifier: NCT00005134.

The marmoset is a fundamental nonhuman primate model for the study of aging, neurobiology, and many other topics. Genetic management of captive marmoset colonies is complicated by frequent chimerism in the blood and other tissues, a lack of tools to enable cost-effective, genome-wide interrogation of variation, and historic mergers and migrations of animals between colonies. We implemented genotype-by-sequencing (GBS) of hair follicle derived DNA (a minimally chimeric DNA source) of 82 marmosets housed at the Southwest National Primate Research Center (SNPRC). Our primary goals were the genetic characterization of our marmoset population for pedigree verification and colony management and to inform the scientific community of the functional genetic makeup of this valuable resource. We used the GBS data to reconstruct the genetic legacy of recent mergers between colonies, to identify genetically related animals whose relationships were previously unknown due to incomplete pedigree information, and to show that animals in the SNPRC colony appear to exhibit low levels of inbreeding. Of the >99,000 single-nucleotide variants (SNVs) that we characterized, >9800 are located within gene regions known to harbor pathogenic variants of clinical significance in humans. Overall, we show the combination of low-resolution (sparse) genotyping using hair follicle DNA is a powerful strategy for the genetic management of captive marmoset colonies and for identifying potential SNVs for the development of biomedical research models.

BACKGROUND: Although COVID-19 infection has been associated with a number of clinical and environmental risk factors, host genetic variation has also been associated with the incidence and morbidity of infection. The CRP gene codes for a critical component of the innate immune system and CRP variants have been reported associated with infectious disease and vaccination outcomes. We investigated possible associations between COVID-19 outcome and a limited number of candidate gene variants including rs1205.

METHODOLOGY/PRINCIPAL FINDINGS: The Strong Heart and Strong Heart Family studies have accumulated detailed genetic, cardiovascular risk and event data in geographically dispersed American Indian communities since 1988. Genotypic data and 91 COVID-19 adjudicated deaths or hospitalizations from 2/1/20 through 3/1/23 were identified among 3,780 participants in two subsets. Among 21 candidate variants including genes in the interferon response pathway, APOE, TMPRSS2, TLR3, the HLA complex and the ABO blood group, only rs1205, a 3' untranslated region variant in the CRP gene, showed nominally significant association in T-dominant model analyses (odds ratio 1.859, 95%CI 1.001-3.453, p = 0.049) after adjustment for age, sex, center, body mass index, and a history of cardiovascular disease. Within the younger subset, association with the rs1205 T-Dom genotype was stronger, both in the same adjusted logistic model and in the SOLAR analysis also adjusting for other genetic relatedness.

CONCLUSION: A T-dominant genotype of rs1205 in the CRP gene is associated with COVID-19 death or hospitalization, even after adjustment for relevant clinical factors and potential participant relatedness. Additional study of other populations and genetic variants of this gene are warranted.