Publications

BACKGROUND: Identifying lipidomic markers of diet quality is needed to inform the development of biomarkers of diet, and to understand the mechanisms driving the diet- coronary heart disease (CHD) association.

OBJECTIVES: This study aimed to identify lipidomic markers of diet quality and examine whether these lipids are associated with incident CHD.

METHODS: Using liquid chromatography-mass spectrometry, we measured 1542 lipid species from 1694 American Indian adults (aged 18-75 years, 62% female) in the Strong Heart Family Study. Participants were followed up for development of CHD through 2020. Information on the past year diet was collected using the Block Food Frequency Questionnaire, and diet quality was assessed using the Alternative Healthy Eating Index-2010 (AHEI). Mixed-effects linear regression was used to identify individual lipids cross-sectionally associated with AHEI. In prospective analysis, Cox frailty model was used to estimate the hazard ratio (HR) of each AHEI-related lipid for incident CHD. All models were adjusted for age, sex, center, education, body mass index, smoking, alcohol drinking, level of physical activity, energy intake, diabetes, hypertension, and use of lipid-lowering drugs. Multiple testing was controlled at a false discovery rate of <0.05.

RESULTS: Among 1542 lipid species measured, 71 lipid species (23 known), including acylcarnitine, cholesterol esters, glycerophospholipids, sphingomyelins and triacylglycerols, were associated with AHEI. Most of the identified lipids were associated with consumption of ω-3 (n-3) fatty acids. In total, 147 participants developed CHD during a mean follow-up of 17.8 years. Among the diet-related lipids, 10 lipids [5 known: cholesterol ester (CE)(22:5)B, phosphatidylcholine (PC)(p-14:0/22:1)/PC(o-14:0/22:1), PC(p-38:3)/PC(o-38:4)B, phosphatidylethanolamine (PE)(p-18:0/20:4)/PE(o-18:0/20:4), and sphingomyelin (d36:2)A] were associated with incident CHD. On average, each standard deviation increase in the baseline level of these 5 lipids was associated with 17%-23% increased risk of CHD (from HR: 1.17; 95% CI: 1, 1.36; to HR: 1.23; 95% CI: 1.05, 1.43).

CONCLUSIONS: In this study, lipidomic markers of diet quality in American Indian adults are found. Some diet-related lipids are associated with risk of CHD beyond established risk factors.

BACKGROUND: Although many studies on the association between dyslipidemia and cardiovascular disease (CVD) exist in older adults, data on the association among adolescents and young adults living with disproportionate burden of cardiometabolic disorders are scarce.

METHODS AND RESULTS: The SHFS (Strong Heart Family Study) is a multicenter, family-based, prospective cohort study of CVD in an American Indian populations, including 12 communities in central Arizona, southwestern Oklahoma, and the Dakotas. We evaluated SHFS participants, who were 15 to 39 years old at the baseline examination in 2001 to 2003 (n=1440). Lipids were measured after a 12-hour fast. We used carotid ultrasounds to detect plaque at baseline and follow-up in 2006 to 2009 (median follow-up=5.5 years). We identified incident CVD events through 2020 with a median follow-up of 18.5 years. We used shared frailty proportional hazards models to assess the association between dyslipidemia and subclinical or clinical CVD, while controlling for covariates. Baseline dyslipidemia prevalence was 55.2%, 73.6%, and 78.0% for participants 15 to 19, 20 to 29, and 30 to 39 years old, respectively. Approximately 2.8% had low-density lipoprotein cholesterol ≥160 mg/dL, which is higher than the recommended threshold for lifestyle or medical interventions in young adults of 20 to 39 years old. During follow-up, 9.9% had incident plaque (109/1104 plaque-free participants with baseline and follow-up ultrasounds), 11.0% had plaque progression (128/1165 with both baseline and follow-up ultrasounds), and 9% had incident CVD (127/1416 CVD-free participants at baseline). Plaque incidence and progression were higher in participants with total cholesterol ≥200 mg/dL, low-density lipoprotein cholesterol ≥160 mg/dL, or non-high-density lipoprotein cholesterol ≥130 mg/dL, while controlling for covariates. CVD risk was independently associated with low-density lipoprotein cholesterol ≥160 mg/dL.

CONCLUSIONS: Dyslipidemia is a modifiable risk factor that is associated with both subclinical and clinical CVD, even among the younger American Indian population who have unexpectedly high rates of significant CVD events. Therefore, this population is likely to benefit from a variety of evidence-based interventions including screening, educational, lifestyle, and guideline-directed medical therapy at an early age.

The generalized estimating equations method (GEE) is commonly applied to analyze data obtained from family studies. GEE is well known for its robustness on misspecification of correlation structure. However, the unbalanced distribution of family sizes and complicated genetic relatedness structure within each family may challenge GEE performance. We focused our research on binary outcomes. To evaluate the performance of GEE, we conducted a series of simulations, on data generated adopting the kinship matrix (correlation structure within each family) from the Strong Heart Family Study (SHFS). We performed a fivefold cross-validation to further evaluate the GEE predictive power on data from the SHFS. A Bayesian modeling approach, with direct integration of the kinship matrix, was also included to contrast with GEE. Our simulation studies revealed that GEE performs well on a binary outcome from families having a relatively simple kinship structure. However, data with a binary outcome generated from families with complex kinship structures, especially with a large genetic variance, can challenge the performance of GEE.

BACKGROUND: Cardiovascular disease (CVD) is a leading cause of morbidity and mortality in American Indian people. In 2022, the American Heart Association developed the Life's Essential 8 goals to promote cardiovascular health (CVH) for Americans, composed of diet, physical activity, nicotine exposure, sleep, body mass index, blood lipids, blood pressure, and blood glucose. We examined whether achievement of Life's Essential 8 goals was associated with incident CVD among SHFS (Strong Heart Family Study) participants.

METHODS AND RESULTS: A total of 2139 SHFS participants without CVD at baseline were included in analyses. We created a composite CVH score based on achievement of Life's Essential 8 goals, excluding sleep. Scores of 0 to 49 represented low CVH, 50 to 69 represented moderate CVH, and 70 to 100 represented high CVH. Incident CVD was defined as incident myocardial infarction, coronary heart disease, congestive heart failure, or stroke. Cox proportional hazard models were used to examine the relationship of CVH and incident CVD. The incidence rate of CVD at the 20-year follow-up was 7.43 per 1000 person-years. Compared with participants with low CVH, participants with moderate and high CVH had a lower risk of incident CVD; the hazard ratios and 95% CIs for incident CVD for moderate and high CVH were 0.52 (95% CI, 0.40-0.68) and 0.25 (95% CI, 0.14-0.44), respectively, after adjustment for age, sex, education, and study site.

CONCLUSIONS: Better CVH was associated with lower CVD risk which highlights the need for comprehensive public health interventions targeting CVH promotion to reduce CVD risk in American Indian communities.

This study investigates correlates of anti-S1 antibody response following COVID-19 vaccination in a U.S. population-based meta-cohort of adults participating in longstanding NIH-funded cohort studies. Anti-S1 antibodies were measured from dried blood spots collected between February 2021-August 2022 using Luminex-based microsphere immunoassays. Of 6245 participants, mean age was 73 years (range, 21-100), 58% were female, and 76% were non-Hispanic White. Nearly 52% of participants received the BNT162b2 vaccine and 48% received the mRNA-1273 vaccine. Lower anti-S1 antibody levels are associated with age of 65 years or older, male sex, higher body mass index, smoking, diabetes, COPD and receipt of BNT16b2 vaccine (vs mRNA-1273). Participants with a prior infection, particularly those with a history of hospitalized illness, have higher anti-S1 antibody levels. These results suggest that adults with certain socio-demographic and clinical characteristics may have less robust antibody responses to COVID-19 vaccination and could be prioritized for more frequent re-vaccination.

BACKGROUND: Chronic lead exposure is associated with both subclinical and clinical cardiovascular disease. We evaluated whether declines in blood lead were associated with changes in systolic and diastolic blood pressure in adult American Indian participants from the SHFS (Strong Heart Family Study).

METHODS AND RESULTS: Lead in whole blood was measured in 285 SHFS participants in 1997 to 1999 and 2006 to 2009. Blood pressure and measures of cardiac geometry and function were obtained in 2001 to 2003 and 2006 to 2009. We used generalized estimating equations to evaluate the association of declines in blood lead with changes in blood pressure; cardiac function and geometry measures were considered secondary. Mean blood lead was 2.04 μg/dL at baseline. After ≈10 years, mean decline in blood lead was 0.67 μg/dL. In fully adjusted models, the mean difference in systolic blood pressure comparing the highest to lowest tertile of decline (>0.91 versus <0.27 μg/dL) in blood lead was -7.08 mm Hg (95% CI, -13.16 to -1.00). A significant nonlinear association between declines in blood lead and declines in systolic blood pressure was detected, with significant linear associations where blood lead decline was 0.1 μg/dL or higher. Declines in blood lead were nonsignificantly associated with declines in diastolic blood pressure and significantly associated with declines in interventricular septum thickness.

CONCLUSIONS: Declines in blood lead levels in American Indian adults, even when small (0.1-1.0 μg/dL), were associated with reductions in systolic blood pressure. These findings suggest the need to further study the cardiovascular impacts of reducing lead exposures and the importance of lead exposure prevention.

[This corrects the article DOI: 10.1016/j.xhgg.2022.100099.].

BACKGROUND: Fibrinogen plays an essential role in blood coagulation and inflammation. Circulating fibrinogen levels may be determined based on interindividual differences in DNA methylation at cytosine-phosphate-guanine (CpG) sites and vice versa.

OBJECTIVES: To perform an EWAS to examine an association between blood DNA methylation levels and circulating fibrinogen levels to better understand its biological and pathophysiological actions.

METHODS: We performed an epigenome-wide association study of circulating fibrinogen levels in 18 037 White, Black, American Indian, and Hispanic participants, representing 14 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. Circulating leukocyte DNA methylation was measured using the Illumina 450K array in 12 904 participants and using the EPIC array in 5133 participants. In each study, an epigenome-wide association study of fibrinogen was performed using linear mixed models adjusted for potential confounders. Study-specific results were combined using array-specific meta-analysis, followed by cross-replication of epigenome-wide significant associations. We compared models with and without CRP adjustment to examine the role of inflammation.

RESULTS: We identified 208 and 87 significant CpG sites associated with fibrinogen levels from the 450K (p < 1.03 × 10-7) and EPIC arrays (p < 5.78 × 10-8), respectively. There were 78 associations from the 450K array that replicated in the EPIC array and 26 vice versa. After accounting for overlapping sites, there were 83 replicated CpG sites located in 61 loci, of which only 4 have been previously reported for fibrinogen. The examples of genes located near these CpG sites were SOCS3 and AIM2, which are involved in inflammatory pathways. The associations of all 83 replicated CpG sites were attenuated after CRP adjustment, although many remained significant.

CONCLUSION: We identified 83 CpG sites associated with circulating fibrinogen levels. These associations are partially driven by inflammatory pathways shared by both fibrinogen and CRP.

PURPOSE: Liver cancer incidence among American Indians/Alaska Natives has risen over the past 20 years. Peripheral blood DNA methylation may be associated with liver cancer and could be used as a biomarker for cancer risk. We evaluated the association of blood DNA methylation with risk of liver cancer.

METHODS: We conducted a prospective cohort study in 2324 American Indians, between age 45 and 75 years, from Arizona, Oklahoma, North Dakota and South Dakota who participated in the Strong Heart Study between 1989 and 1991. Liver cancer deaths (n = 21) were ascertained using death certificates obtained through 2017. The mean follow-up duration (SD) for non-cases was 25.1 (5.6) years and for cases, 11.0 (8.8) years. DNA methylation was assessed from blood samples collected at baseline using MethylationEPIC BeadChip 850 K arrays. We used Cox regression models adjusted for age, sex, center, body mass index, low-density lipoprotein cholesterol, smoking, alcohol consumption, and immune cell proportions to examine the associations.

RESULTS: We identified 9 CpG sites associated with liver cancer. cg16057201 annotated to MRFAP1) was hypermethylated among cases vs. non-cases (hazard ratio (HR) for one standard deviation increase in methylation was 1.25 (95% CI 1.14, 1.37). The other eight CpGs were hypomethylated and the corresponding HRs (95% CI) ranged from 0.58 (0.44, 0.75) for cg04967787 (annotated to PPRC1) to 0.77 (0.67, 0.88) for cg08550308. We also assessed 7 differentially methylated CpG sites associated with liver cancer in previous studies. The adjusted HR for cg15079934 (annotated to LPS1) was 1.93 (95% CI 1.10, 3.39).

CONCLUSIONS: Blood DNA methylation may be associated with liver cancer mortality and may be altered during the development of liver cancer.

BACKGROUND. The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon method to calculate signal fat fraction (FF) from conventional T1-weighted in- and opposed-phase (IOP) images, although signal FF is prone to biases, leading to inaccurate quantification. OBJECTIVE. The purpose of this study was to compare hepatic fat quantification by use of PDFF inferred from conventional T1-weighted IOP images and deep-learning convolutional neural networks (CNNs) with quantification by use of two-point Dixon signal FF with CSE-MRI PDFF as the reference standard. METHODS. This study entailed retrospective analysis of data from 292 participants (203 women, 89 men; mean age, 53.7 ± 12.0 [SD] years) enrolled at two sites from September 1, 2017, to December 18, 2019, in the Strong Heart Family Study (a prospective population-based study of American Indian communities). Participants underwent liver MRI (site A, 3 T; site B, 1.5 T) including T1-weighted IOP MRI and CSE-MRI (used to reconstruct CSE PDFF and CSE R2* maps). With CSE PDFF as reference, a CNN was trained in a random sample of 218 (75%) participants to infer voxel-by-voxel PDFF maps from T1-weighted IOP images; testing was performed in the other 74 (25%) participants. Parametric values from the entire liver were automatically extracted. Per-participant median CNN-inferred PDFF and median two-point Dixon signal FF were compared with reference median CSE-MRI PDFF by means of linear regression analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. The code is publicly available at github.com/kang927/CNN-inference-of-PDFF-from-T1w-IOP-MR. RESULTS. In the 74 test-set participants, reference CSE PDFF ranged from 1% to 32% (mean, 11.3% ± 8.3% [SD]); reference CSE R2* ranged from 31 to 457 seconds-1 (mean, 62.4 ± 67.3 seconds-1 [SD]). Agreement metrics with reference to CSE PDFF for CNN-inferred PDFF were ICC = 0.99, bias = -0.19%, 95% limits of agreement (LoA) = (-2.80%, 2.71%) and for two-point Dixon signal FF were ICC = 0.93, bias = -1.11%, LoA = (-7.54%, 5.33%). CONCLUSION. Agreement with reference CSE PDFF was better for CNN-inferred PDFF from conventional T1-weighted IOP images than for two-point Dixon signal FF. Further investigation is needed in individuals with moderate-to-severe iron overload. CLINICAL IMPACT. Measurement of CNN-inferred PDFF from widely available T1-weighted IOP images may facilitate adoption of hepatic PDFF as a quantitative bio-marker for liver fat assessment, expanding opportunities to screen for hepatic steatosis and nonalcoholic fatty liver disease.