Urinary Metal Levels and Coronary Artery Calcification: Longitudinal Evidence in the Multi-Ethnic Study of Atherosclerosis

Abstract

Background: Exposure to metals, a newly recognized risk factor for cardiovascular disease (CVD), could be related to atherosclerosis progression.

Objectives: The authors hypothesized that higher urinary levels of nonessential (cadmium, tungsten, uranium) and essential (cobalt, copper, zinc) metals previously associated with CVD would be associated with baseline and rate of change of coronary artery calcium (CAC) progression, a subclinical marker of CVD in MESA (Multi-Ethnic Study of Atherosclerosis).

Methods: We analyzed data from 6,418 MESA participants with spot urinary metal levels at baseline (2000-2002) and 1 to 4 repeated, continuous measures of CAC over a 10-year period. We used linear mixed-effect models to assess the association of baseline urinary metal levels with baseline CAC and cumulative change in CAC over a 10-year period. Urinary metals (μg/g creatinine) and CAC were log transformed. Models were adjusted for baseline sociodemographic factors, estimated glomerular filtration rate, lifestyle factors, and clinical factors.

Results: At baseline, the median CAC was 6.3 (Q1-Q3: 0.7-58.2). Comparing the highest to lowest quartile of urinary cadmium, CAC levels were 51% (95% CI: 32%, 74%) higher at baseline and 75% (95% CI: 47%, 107%) higher over the 10-year period. For urinary tungsten, uranium, and cobalt, the corresponding CAC levels over the 10-year period were 45% (95% CI: 23%, 71%), 39% (95% CI: 17%, 64%), and 47% (95% CI: 25%, 74%) higher, respectively, with no difference for models with and without adjustment for clinical factors. For copper and zinc, the corresponding estimates dropped from 55% to 33% and from 85% to 57%, respectively, after adjustment for clinical factors. The associations of metals with CAC were comparable in magnitude to those for classical CVD risk factors.

Conclusions: Exposure to metals was generally associated with extent of coronary calcification at baseline and follow-up. These findings support that metals are associated with the progression of atherosclerosis, potentially providing a novel strategy for the prevention and treatment of atherosclerosis progression.

Keywords: cadmium; cardiovascular disease; cobalt; copper; coronary artery calcification; longitudinal; metals; mixed models; prospective; tungsten; uranium; zinc.

FIGURE 1. Urinary Metal Level Distributions by Participant Characteristics

Median (Q1-Q3) of urinary metal levels (μg/g creatinine) among MESA (Multi-Ethnic Study of Atherosclerosis) participants (n = 6,418) by participant characteristic for nonessential metals cadmium (Cd), tungsten (W), and uranium (U), and essential metals cobalt (Co), copper (Cu), and zinc (Zn). Points represent the median urine metal level and lines correspond to the IQR overall and for each subgroup at baseline. The n for each group is on the y-axis. The dotted line represents the overall median urine metal level. BMI = body mass index; CAC = coronary artery calcification.

FIGURE 2. Flexible Dose-Response of Urinary Metal Levels and CAC

Geometric mean ratios (GMRs) (95% CI) of baseline estimates (blue lines and shaded areas) and 10-year cumulative changes (orange lines and shaded areas) in spatially weighted coronary artery calcium (CAC-SW) scores by log-transformed urinary metal levels (μg/g creatinine) among MESA participants (n = 6,418), modeled as restricted quadratic splines with knots at the 10th (reference), 50th, and 90th percentiles. The histograms represent the distribution of each metal at baseline. Models were adjusted for age, sex, race and ethnicity, study site, education, estimated glomerular filtration rate, smoking status, pack-years, physical activity, BMI, systolic blood pressure, antihypertensive medication, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, lipid-lowering medications, and diabetes status. ^aGMRs correspond to exponentiating the coefficient obtained from the splines in the regression model. Percent differences in Table 2 can be obtained by subtracting one from the GMR and multiplying it by 100. Abbreviations as in Figure 1.

FIGURE 3. Association Between the Metal Mixture and CAC

The percent difference (95% credibility intervals) of the overall association between the urinary metal mixture (cadmium, tungsten, uranium, cobalt, copper, and zinc) and CAC-SW. The overall association compares the value of the exposure response function when all metals are at a particular percentile (25th to 95th, by 5) as compared to when all predictors are at their 25th percentile. Models were adjusted for age, sex, race and ethnicity, study site, education, estimated glomerular filtration rate, smoking status, pack-years, physical activity, BMI, systolic blood pressure, antihypertensive medication, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, lipid-lowering medications, and diabetes status. Other abbreviations as in Figures 1 and 2.

CENTRAL ILLUSTRATION. Urinary Metals and Repeated Measures of Coronary Artery Calcification in the Multi-Ethnic Study of Atherosclerosis

In a longitudinal study design in MESA (Multi-Ethnic Study of Atherosclerosis), linear mixed-effect models were used to assess baseline metal exposure, as measured in urine using inductively coupled plasma mass spectrometry (ICP-MS), and repeated measures of coronary artery calcification (CAC) over a 10-year follow-up period among 6,418 participants free of clinical cardiovascular disease at baseline (panel 1). Metal exposure may contribute to calcification in the arteries over time through inflammation, oxidative stress, endothelial dysfunction, or lipid metabolism (panel 2). The flexible dose response curves show geometric mean ratios of 10-year cumulative changes in spatially weighted coronary artery calcium (CAC-SW) scores by urinary metal level z-scores modeled as restricted quadratic splines with knots at the 10th, 50th, and 90th percentiles; the reference value was set at the 10th percentile (panel 3). Models were adjusted for age, sex, race and ethnicity, study site, education, estimated glomerular filtration rate, smoking status, pack-years, physical activity, body mass index, systolic blood pressure, antihypertensive medication, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, lipid-lowering medications, and diabetes status. Illustrations © by Biotic Artlab, 2024.