Associations of thiocyanate, nitrate, and perchlorate exposure with dyslipidemia: a cross-sectional, population-based analysis

doi:10.21203/rs.3.rs-1860994/v1

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Associations of thiocyanate, nitrate, and perchlorate exposure with dyslipidemia: a cross-sectional, population-based analysis

https://doi.org/10.21203/rs.3.rs-1860994/v1

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The aim of this study was to assess the associations of urinary thiocyanate, nitrate, and perchlorate concentrations with dyslipidemia, individually and in combination, which has not previously been studied. Data from the 2001–2002 and 2005–2016 National Health and Nutrition Examination Surveys (NHANES) were analyzed in this cross-sectional study. The dependent variables were continuous serum lipid variables (triglycerides [TG], total cholesterol [TC], low-density lipoprotein cholesterol [LDL-C], high-density lipoprotein cholesterol [HDL-C], non-HDL-C, and apolipoprotein B [Apo B]) and binary serum lipid variables, with the latter reflecting dyslipidemia (elevated TG, ≥ 150 mg/dL; elevated TC, ≥ 200 mg/dL; elevated LDL-C, ≥ 130 mg/dL; lowered HDL-C, < 40 mg/dL in men and < 50 mg/dL in women; elevated non-HDL-C, ≥ 160 mg/dL; and elevated Apo B, ≥ 130 mg/dL). Multivariate logistic, linear, and weighted quantile sum (WQS) regression analyses were used to explore the associations of thiocyanate, nitrate, and perchlorate with the continuous and binary serum lipid variables. The linearity of the associations with the binary serum lipid variables was assessed using restricted cubic spline (RCS) regression. A total of 15,563 adults were included in the analysis. The multivariate linear and logistic regression analyses showed that thiocyanate was positively associated with multiple continuous (TG, TC, LDL-C, non-HDL-C, and Apo B, but not HDL-C) and binary (elevated TG, TC, LDL-C, and non-HDL-C) serum lipid variables, whereas perchlorate was negatively associated with elevated LDL-C. Multivariate RCS logistic regression revealed a linear dose–response relationship between thiocyanate and elevated TG, TC, LDL-C, non-HDL-C, and Apo B, but a nonlinear relationship with lowered HDL-C (inflection point = 1.622 mg/L). WQS regression showed that a mixture of thiocyanate, nitrate, and perchlorate was positively associated with all binary serum lipid variables except for Apo B. Our findings indicate that urinary thiocyanate, nitrate, and perchlorate concentrations, individually and in combination, were associated with dyslipidemia.

thiocyanate

nitrate

perchlorate

lipid profiles

dyslipidemia

Cardiovascular disease (CVD) is the leading cause of mortality in every region of the world (Roth et al. 2020). Dyslipidemia is prevalent in the general population and increases the development and progression of atherosclerotic CVD (Virani et al. 2020). There is a significant correlation between serum total cholesterol (TC) and atherosclerotic CVD (Arnett et al. 2019). Low-density lipoprotein cholesterol (LDL-C) is the primary atherogenic type of cholesterol (Arnett et al. 2019). LDL is primarily responsible for transporting triglycerides (TG), and LDL-C can induce atherosclerosis (AS) (Arnett et al. 2019). Similarly, research suggests a relationship between apolipoprotein B (Apo B) and the development of AS (Marston et al. 2022). In contrast, high-density lipoprotein cholesterol (HDL-C) reduces the progression of AS (Barter &Genest 2019). Moreover, several dyslipidemia management guidelines propose that lowering non-HDL-C should be the primary therapeutic target (Pearson et al. 2021, Stone et al. 2014, Visseren et al. 2021). In addition to atherosclerotic CVD, dyslipidemia is related to hypertension, diabetes, valvular heart disease, chronic renal disease, metabolic syndrome, and nonalcoholic fatty liver disease (Bloomgarden 2004, Kane et al. 2021, Katsiki et al. 2016, Kotsis et al. 2018, Mata et al. 2021, Slinin et al. 2012). To successfully control the progression of AS and CVD events, the detection and treatment of dyslipidemia at an early stage is crucial (Virani et al. 2020).

Thiocyanate, nitrate, and perchlorate are common in nature. Thiocyanate is a pseudohalide that is widely found in people (Chiang et al. 2016). It is a primary metabolite of cigarette smoke and is extensively utilized in furniture and electronics manufacturing (Jain 2016). Nitrates are employed as precursors of nitrites and are widely used as agricultural fertilizers and food preservatives (Sindelar &Milkowski 2012). In the human diet, drinking water and vegetables account for > 80% of the nitrate exposure (Salehzadeh et al. 2020). Perchlorate is both a manufactured pollutant and a naturally occurring chemical in the environment (Dasgupta et al. 2005, Wan et al. 2015). It is widely used for military and industrial purposes and has been found in milk and vegetables (Dasgupta et al. 2005, Wan et al. 2015). There is emerging evidence that the general public may be exposed to these three toxins through many environmental and dietary sources. Urinary thiocyanate, nitrate, and perchlorate concentrations are extensively utilized as well-established biomarkers for biomonitoring and assessing individuals’ internal exposure status (Liu et al. 2017, Mervish et al. 2016, Yu et al. 2022a, Zhu et al. 2021).

A growing body of in vivo and in vitro evidence shows that thiocyanate, nitrate, and perchlorate may have negative impacts on thyroid function (García Torres et al. 2022, King et al. 2022, Leung et al. 2014, Willemin &Lumen 2017), cancer (Carvalho et al. 2021, Picetti et al. 2022, Said Abasse et al. 2022, Shiue 2015, Wang et al. 2022a, Wang et al. 2018, Zhang et al. 2018), oral health (Yu et al. 2022b, a), as well as asthma and allergic reactions (Bose et al. 2017, Nadif et al. 2014, Zhu et al. 2021). Furthermore, thiocyanate, nitrate, and perchlorate have been linked to CVD (Bondonno et al. 2021, Wang et al. 2022b) and its risk factors (obesity (Ghasemi &Jeddi 2017, Zhu et al. 2019) and high fasting glucose and glycated hemoglobin A1c, and insulin resistance (Liu et al. 2017, Parslow et al. 1997)). Environmental contaminants may play a significant role in the development of dyslipidemia, according to a growing number of studies (Gaio et al. 2019, He et al. 2018, Zhu et al. 2022). However, there is currently no evidence linking perchlorate, nitrate, or thiocyanate exposure to dyslipidemia risk. We hypothesized a relationship between thiocyanate, nitrate, and perchlorate exposure and dyslipidemia. We analyzed the associations of urinary thiocyanate, nitrate, and perchlorate concentrations with continuous and binary serum lipid variables (with the latter reflecting dyslipidemia) in the general adult population from the 2001–2002 and 2005–2016 United States National Health and Nutrition Examination Surveys (NHANES).

2.1 Study population

NHANES are cross-sectional surveys with 2-year cycles; they use a multi-stage, cluster-sampling design to ensure nationally representative samples (https://wwwn.cdc.gov/nchs/nhanes/default.aspx). The NHANES research protocols were approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board, and all participants provided written informed consent.

We analyzed descriptive data from the 2001–2002 and 2005–2016 NHANES. We enrolled eligible participants with complete data on urinary thiocyanate, nitrate, and perchlorate. Exclusion criteria were as follows: 1) missing data on serum lipid variables, 2) taking prescribed medicine for lipids, 3) aged < 18 years, and 4) pregnancy.

2.2 Assessment of urinary thiocyanate, nitrate, and perchlorate

Urine samples were stored at -20°C or less until examination. Thiocyanate, nitrate, and perchlorate concentrations in the urine were quantified using electrospray ion chromatography-tandem mass spectrometry. The limits of detection (LOD) of urinary thiocyanate, nitrate, and perchlorate were 0.05 µg/L, 0.70 mg/L, and 0.02 mg/L, respectively. All concentrations below the LOD were replaced by an LOD value divided by the square root of 2 (LOD/√2). The NHANES website provides details on the analytical processes employed (https://wwwn.cdc.gov/nchs/data/nhanes/2015-2016/labmethods/PERNT-PERNTS-I-MET-508.pdf).

2.3 Assessment of serum lipid variables

In NHANES, fasting serum samples were processed and stored until analysis. TC and TG were measured enzymatically. HDL-C was determined using the direct HDL-C immunoassay method. LDL-C was computed using the Friedewald formula ([LDL-C] = [TC]−[HDL-C]−[TG/5]) (Mehta et al. 2018). Non-HDL-C was computed as TC minus HDL-C (Mach et al. 2020). Apo B was measured using an immunochemical assay. The binary serum lipid variables were created using the following cutoff values, reflecting dyslipidemia: elevated TG, ≥ 150 mg/dL; elevated TC, ≥ 200 mg/dL; elevated LDL-C, ≥ 130 mg/dL; lowered HDL-C, < 40 mg/dL in men and < 50 mg/dL in women; elevated non-HDL-C, ≥ 160 mg/dL; and elevated Apo B, ≥ 130 mg/dL (Anonymous 2002, Jacobson et al. 2015, Welsh et al. 2010).

2.4 Covariates

In NHANES, data collection was carried out using a standardized questionnaire during a household interview, two 24 -hour recall interviews (for assessing energy intake), and a medical evaluation (including urine tests based on urine spot samples and blood tests). We selected the following potential confounding covariates linked to dyslipidemia: age, gender, race, education level, smoking, alcohol use, poverty, body mass index (BMI), physical activity, energy intake, urinary creatinine, uric acid, estimated glomerular filtration rate (eGFR), diabetes mellitus, and hypertension.

The categories for race/ethnicity were “Mexican American,” “Other Hispanic,” “Non-Hispanic White,” “Non-Hispanic Black,” and “Other”. Education levels were categorized as “below high school,” “high school,” and “above high school”. Poverty was assessed based on the poverty income ratio (PIR) and defined as PIR < 1 for a family. Individuals with cotinine levels > 14 ng/mL were classified as smokers (Jarvis et al. 1987). Individuals who consumed ≥ 12 alcoholic drinks in a single calendar year were considered alcohol users. Energy intake was calculated by averaging the two values from the two 24-hour recall interviews. Physical activity was classified as “active”, “insufficiently active”, or “inactive” (Pate et al. 1995). Uric acid in blood samples were measured using laboratory tests. The eGFR was computed using the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation (Levey et al. 2009). Descriptions of each variable are presented at https://wwwn.cdc.gov/Nchs/Nhanes/continuousnhanes/.

2.5 Statistical analysis

In accordance with National Center for Health Statistics recommendations, weighted analyses were conducted to provide reliable national estimates (https://wwwn.cdc.gov/nchs/nhanes/tutorials/default.aspx). The participant characteristics are presented as median (interquartile range [IQR]) or frequency (percentage) for continuous and categorical variables, respectively. Urinary thiocyanate, nitrate, and perchlorate concentrations had skewed distributions and so underwent log2 transformation (for the continuous dependent variable analyses). They were also divided into four quartiles (for the categorical dependent variable analyses). Correlation coefficients between log2-transformed thiocyanate, nitrate, and perchlorate were estimated using Spearman rank correlation analysis. All statistical analyses were conducted in R (version 4.1.0), and p < 0.05 (two-sided) was deemed significant.

Three sequential multivariate linear regression models (model 1 covariates: age, gender, race, and urinary creatinine; model 2 covariates: model 1 plus education level, poverty, smoking, and alcohol use; and model 3 covariates: model 2 plus BMI, energy intake levels, physical activity, eGFR, uric acid, diabetes, and hypertension) with increasing levels of adjustment for confounding variables were employed to explore the associations of urinary thiocyanate, nitrate, and perchlorate concentrations with the following continuous serum lipid variables: TG, TC, LDL-C, non-HDL-C, and Apo B, and HDL-C. Three sequential multivariate logistic regression models (model covariates: age, gender, race, education level, poverty, smoking, and alcohol use, body mass index, energy intake levels, physical activity, eGFR, uric acid, urinary creatinine, diabetes, and hypertension) were also employed to explore the associations of urinary thiocyanate, nitrate, and perchlorate concentrations with the following binary serum lipid variables: elevated TG, TC, LDL-C, non-HDL-C, and Apo B, and lowered HDL-C. Sensitivity analyses were performed using urinary creatinine-adjusted thiocyanate, nitrate, and perchlorate in order to correct for differences in urine dilution in the urine spot samples (Ko et al. 2014).

Restricted cubic spline (RCS) logistic regression was utilized to investigate the dose–response relationships between log2-transformed thiocyanate, nitrate, and perchlorate and the binary serum lipid variables, using three knots (10th, 50th, and 90th percentiles). The threshold inflection point of the linear relationship was calculated using a segmented regression to fit the piecewise-linear associations of the independent variables with the dependent variables, as described previously (Li et al. 2022).

As there were significant correlations among urinary thiocyanate, nitrate, and perchlorate, weighted quantile sum (WQS) regression was conducted using the “gWQS” R package to assess the associations of the mixture of urinary thiocyanate, nitrate, and perchlorate with binary and continuous serum lipid variables. For this analysis, each chemical (thiocyanate, nitrate, and perchlorate) was given a weight within a WQS index that indicated how much of a contribution each chemical had made to the overall association in the regression. Specifically, we established the WQS index according to deciles of urinary thiocyanate, nitrate, and perchlorate concentrations. We used 40% of the data as the test set and the remaining 60% as the validation set, with a total of 10,000 bootstrap samplings.

3.1 Participant characteristics

A total of 71,975 individuals participated in NHANES in 2001–2002 and 2005–2016, 42,874 of whom had missing data on urinary thiocyanate, nitrate, and/or perchlorate. We subsequently excluded participants with missing serum lipid data (n = 2,660), those taking prescribed medicine for lipids (n = 2,992), those aged < 18 years (n = 7,340), and those who were pregnant (n = 546). This left 15,563 participants for the analyses of HDL-C, TC, and non-HDL-C, 7,236 participants for the analyses of TG and LDL-C, and 6,732 participants for the analysis of Apo B (Fig. 1).

Table 1 presents the survey-weighted characteristics of the enrolled participants. The weighted sample had a median age of 42.0 years and 51.2% of individuals were female. The proportion of individuals with elevated TG (≥ 150 mg/dL), TC (≥ 200 mg/dL), LDL-C (≥ 130 mg/dL), non-HDL-C (≥ 160 mg/dL), and Apo B (≥ 130 mg/dL) and lowered HDL-C (< 40 mg/dL in men and < 50 mg/dL in women) was 23.5%, 44.2%, 34.2%, 31.5%, 8.0%, and 29.3%, respectively.

Table 1

Survey-weighted, sociodemographic and health status characteristics of adult NHANES 2001–2002 and 2005–2016 participants with available blood ethylene oxide data (n = 15,563).
Variable	Median (IQR) or N (%)
Age, years	42.0 (30.0, 54.0)
Male, %	7833 (48.8%)
Education level, %
Below high school	4145 (16.9%)
High school	3576 (22.5%)
Above high school	7842 (60.6%)
Race/ethnicity, %
Mexican American	2968 (9.1%)
Other Hispanic	1356 (5.7%)
Non-Hispanic White	6778 (67.0%)
Non-Hispanic Black	3286 (11.1%)
Other race	1175 (7.1%)
Poverty, %	3381 (14.8%)
Smoking, %	4135 (26.8%)
Alcohol use, %	11218 (76.7%)
Body mass index, kg/m²	27.1 (23.6, 31.7)
Physical activity, %
Inactive	3704 (19.5%)
Insufficiently active	5352 (34.6%)
Active	6507 (45.9%)
Energy intake, kcal/day	2059.0 (1546.0, 2713.0)
Uric acid, mg/dL	5.3 (4.3, 6.3)
eGFR, ml/min/1.73 m²	99.1 (84.4, 112.7)
Urinary creatinine, mg/dL	107.0 (57.0, 166.0)
Hypertension, %	3995 (23.3%)
Diabetes, %	1103 (5.3%)
Triglyceride, mg/dL	100.0 (69.0, 145.0)
Total cholesterol, mg/dL	194.0 (167.0, 221.0)
Low-density lipoprotein cholesterol, mg/dL	115.0 (93.0, 139.0)
High-density lipoprotein cholesterol, mg/dL	51.0 (42.0, 62.0)
Non-high-density lipoprotein cholesterol, mg/dL	139.0 (113.0, 168.0)
Apolipoprotein B, mg/dL	91.0 (75.0, 109.0)
Elevated TG (≥ 150 mg/dL), %	1733 (23.5%)
Elevated TC (≥ 200 mg/dL), %	6611 (44.2%)
Elevated LDL-C (≥ 130 mg/dL), %	2348 (34.2%)
Lowered HDL (< 40 mg/dL in men and < 50 mg/dL in women), %	4735 (29.3%)
Elevated Non-HDL-C (≥ 160 mg/dL), %	4793 (31.5%)
Elevated Apo B (≥ 130 mg/dL), %	588 (8.0%)
Data are presented as median (IQR) or n (%); sampling weights were applied for calculation of demographic descriptive statistics. N reflects the study sample, whereas percentages reflect the survey-weighted data. eGFR, estimated glomerular filtration rate.

3.2 Distributions and correlations of thiocyanate, nitrate, and perchlorate

Table S1 details the detection limits and distributions of thiocyanate, nitrate, and perchlorate. The detection rates for thiocyanate, nitrate, and perchlorate were 100%, 99.8%, and 99.9%, respectively. The median thiocyanate, nitrate, and perchlorate concentrations were 3.10 (IQR 1.68, 5.56) µg/L, 46.00 (IQR 26.10, 73.30) mg/L, and 1.20 (IQR 0.57, 2.74) mg/L, respectively. Moderate-to-strong correlations were observed for most of the associations among creatinine, perchlorate, nitrate, and thiocyanate (r ranged from 0.38 to 0.68), while a weak correlation was observed between perchlorate and thiocyanate (r = 0.24, all p < 0.001) (Figure S1).

3.3 Associations of thiocyanate, nitrate, and perchlorate with continuous serum lipid variables

Multivariate linear regression was used to evaluate the associations of continuous (log2-transformed) and categorical (quartiles) thiocyanate, nitrate, and perchlorate variables with continuous serum lipid variables (Tables S2 and 2). Regarding the continuous independent variable/continuous dependent variable analyses, log2-transformed thiocyanate was significantly positively associated with TG (Model 3: β = 3.13; 95% CI: 1.46, 4.80), TC (Model 3: β = 1.70; 95% CI: 1.02, 2.38), LDL-C (Model 3: β = 1.35; 95% CI: 0.60, 2.13), non-HDL-C (Model 3: β = 1.85; 95% CI: 1.16, 2.53), and Apo B (Model 3: β = 0.91; 95% CI: 0.25, 1.58), after adjustment for all covariates (Table S2). Additionally, log2-transformed perchlorate was significantly negatively associated with Apo B (Model 3: β=-0.79; 95% CI: -1.47, -0.11) and log2-transformed nitrate was significantly negatively associated with TG (Model 3: β=-2.97; 95% CI: -5.63, -0.31), after adjustment for all covariates (Table S2).

Regarding the categorical independent variable/continuous dependent variable analyses, with increasing thiocyanate quartiles, TG, TC, LDL-C, non-HDL-C, and Apo B (but not HDL-C) declined monotonically, after adjustment for all covariates (p for trend < 0.01) (Table 2). More specifically, the highest thiocyanate quartile (relative to the lowest quartile) was significantly positively associated with TG (β = 12.71, 95% CI: 3.97, 21.44, p for trend = 0.006), TC (β = 6.98, 95% CI: 3.72, 10.25, P for trend < 0.001), LDL-C (β = 5.52, 95% CI: 1.54, 9.51, P for trend = 0.002), non-HDL-C (β = 7.36, 95% CI: 4.00, 10.72, P for trend < 0.001), and Apo B (β = 4.30, 95% CI: 1.02, 7.60, P for trend = 0.006) after adjustment for all covariates. In contrast, the highest perchlorate quartile was significantly negatively associated with Apo B (β=-2.29, 95% CI: -4.58, -0.01, P for trend = 0.069). No significant associations were observed between the highest nitrate quartile and continuous serum lipid variables. Regarding the sensitivity analysis, similar results were observed for the associations of creatinine-adjusted thiocyanate, nitrate, and perchlorate quartiles with continuous serum lipid variables (Table S3).

Table 2

Multiple linear regression associations of urinary perchlorate, nitrate, and thiocyanate quartiles with lipid profiles in adults.
	TG (n = 7,236)	TC (n = 15,563)	LDL-C (n = 7,236)	HDL (n = 15,563)	Non-HDL-C (n = 15,563)	Apo B (n = 6,732)
	β (95%CI)	β (95%CI)	β (95%CI)	β (95%CI)	β (95%CI)	β (95%CI)
Thiocyanate, mg/L
Quartile 1	0.00	0.00	0.00	0.00	0.00	0.00
Quartile 2	0.35 (-5.02, 5.72)	0.99 (-1.70, 3.68)	-0.08 (-3.41, 3.26)	1.03 (-0.12, 2.17)	-0.04 (-2.73, 2.65)	-0.19 (-2.35, 1.97)
Quartile 3	8.72 (2.20, 15.26) ^**	4.14 (1.40, 6.88) ^**	0.83 (-2.55, 4.21)	0.36 (-0.67, 1.40)	3.78 (1.12, 6.43) ^**	0.85 (-1.53, 3.24)
Quartile 4	12.71 (3.97, 21.44) ^**	6.98 (3.72, 10.25) ^***	5.52 (1.54, 9.51) ^**	-0.38 (-1.64, 0.88)	7.36 (4.00, 10.72) ^***	4.30 (1.02, 7.60) ^*
P for trend	0.006	< 0.001	0.002	0.090	< 0.001	0.006
Nitrate, mg/L
Quartile 1	0.00	0.00	0.00	0.00	0.00	0.00
Quartile 2	1.95 (-4.54, 8.43)	-0.92 (-3.77, 1.94)	-2.17 (-5.79, 1.45)	-1.18 (-2.41, 0.04)	0.27 (-2.62, 3.15)	-0.95 (-3.29, 1.39)
Quartile 3	-1.52 (-9.20, 6.16)	-0.46 (-3.95, 3.03)	-0.96 (-4.85, 2.92)	-1.15 (-2.43, 0.13)	0.69 (-2.94, 4.32)	-0.62 (-3.39, 2.16)
Quartile 4	-7.37 (-15.51, 0.76)	-2.03 (-5.94, 1.88)	-1.59 (-6.45, 3.26)	-0.93 (-2.42, 0.57)	-1.10 (-5.15, 2.94)	-0.79 (-4.35, 2.79)
P for trend	0.014	0.272	0.806	0.637	0.378	0.852
Perchlorate, µg/L
Quartile 1	0.00	0.00	0.00	0.00	0.00	0.00
Quartile 2	4.59 (-0.44, 9.62)	0.47 (-1.95, 2.88)	-1.02 (-4.12, 2.08)	0.18 (-0.94, 1.30)	0.28 (-2.17, 2.74)	-0.32 (-2.45, 1.82)
Quartile 3	3.64 (-2.40, 9.67)	-0.96 (-3.85, 1.93)	-4.07 (-8.13, -0.02) ^*	-0.64 (-1.67, 0.39)	-0.31 (-3.19, 2.56)	-2.12 (-4.42, 0.19)
Quartile 4	4.32 (-2.13, 10.77)	-1.05 (-4.07, 1.98)	-2.79 (-6.27, 0.68)	-0.60 (-1.72, 0.53)	-0.45 (-3.32, 2.42)	-2.29 (-4.58, -0.01) ^*
P for trend	0.487	0.337	0.166	0.136	0.639	0.069
Model was adjusted as age, sex, race, education level, poverty, smoking, and alcohol use, body mass index, energy intake levels, physical activity, eGFR, uric acid, urinary creatinine, diabetes, and hypertension.
HDL-C, high-density lipoprotein cholesterol; TC, total cholesterol; TG, triglyceride; LDL-C, low-density lipoprotein cholesterol; Non-HDL-C, non-high-density lipoprotein cholesterol; Apo B, apolipoprotein B; CI, confidence interval; Ref., reference; ^* p < 0.05, ^ p < 0.01 and ^* p < 0.001.

3.4 Associations of thiocyanate, nitrate, and perchlorate with binary serum lipid variables

Multivariate logistic regression was used to assess the associations of thiocyanate, nitrate, and perchlorate quartiles with binary serum lipid variables (elevated TG, TC, LDL-C, non-HDL-C, and Apo B and lowered HDL-C) (Table 3). Thiocyanate quartiles were significantly positively associated with elevated TG (P for trend = 0.002), elevated TC (P for trend < 0.001), elevated LDL-C (P for trend = 0.011), and elevated non-HDL-C (P for trend < 0.001). More specifically, the ORs for the highest thiocyanate quartile (relative to the lowest quartile) were 1.64 (95% CI: 1.17, 2.28), 1.41 (95% CI: 1.18, 1.69), 1.31 (95% CI: 1.02, 1.67), and 1.46 (95% CI: 1.20, 1.78), respectively. In contrast, perchlorate quartiles were negatively associated with elevated LDL-C, and the ORs for quartiles 2, 3, and 4 (relative to the lowest quartile) were 0.82 (95% CI: 0.66, 1.01), 0.68 (95% CI: 0.52, 0.88), and 0.77 (95% CI: 0.61, 0.97). No significant associations were observed between nitrate and binary serum lipid variables. Regarding the sensitivity analysis, consistent results were observed for the associations of creatinine-adjusted thiocyanate, nitrate, and perchlorate quartiles with binary serum lipid variables (Table S4).

Table 3

Multiple logistic regression associations of urinary perchlorate, nitrate, and thiocyanate quartiles with dyslipidemia in adults.
	Elevated TG (n = 7,236)	Elevated TC (n = 15,563)	Elevated LDL-C (n = 7,236)	Lowered HDL (n = 15,563)	Elevated Non-HDL-C (n = 15,563)	Elevated Apo B (n = 6,732)
	OR (95%CI)	OR (95%CI)	OR (95%CI)	OR (95%CI)	OR (95%CI)	OR (95%CI)
Thiocyanate, mg/L
Quartile 1	1.00	1.00	1.00	1.00	1.00	1.00
Quartile 2	0.95 (0.75–1.21)	1.15 (0.99–1.33)	1.00 (0.80–1.25)	0.85 (0.73–0.99) ^*	1.10 (0.94–1.29)	1.01 (0.69–1.46)
Quartile 3	1.45 (1.11–1.90) ^**	1.22 (1.07–1.40) ^**	0.99 (0.78–1.26)	1.02 (0.88–1.17)	1.21 (1.02–1.43) ^*	1.21 (0.82–1.79)
Quartile 4	1.64 (1.17–2.28) ^**	1.41 (1.18–1.69) ^***	1.31 (1.02–1.67) ^*	1.19 (0.99–1.43)	1.46 (1.20–1.78) ^***	1.60 (0.97–2.66)
P for trend	0.002	< 0.001	0.011	0.004	< 0.001	0.062
Nitrate, mg/L
Quartile 1	1.00	1.00	1.00	1.00	1.00	1.00
Quartile 2	1.17 (0.90–1.52)	1.03 (0.88–1.20)	0.83 (0.65–1.08)	1.14 (0.96–1.36)	1.02 (0.86–1.21)	0.98 (0.63–1.50)
Quartile 3	1.10 (0.80–1.53)	1.01 (0.86–1.20)	0.83 (0.64–1.07)	1.14 (0.95–1.36)	1.03 (0.83–1.27)	1.13 (0.73–1.73)
Quartile 4	0.85 (0.61–1.19)	0.98 (0.81–1.20)	0.80 (0.59–1.10)	1.14 (0.91–1.11)	0.89 (0.71–1.11)	1.43 (0.84–2.42)
P for trend	0.080	0.656	0.361	0.545	0.114	0.091
Perchlorate, µg/L
Quartile 1	1.00	1.00	1.00	1.00	1.00	1.00
Quartile 2	1.12 (0.87–1.43)	0.98 (0.85–1.14)	0.82 (0.66–1.01)	0.95 (0.81–1.11)	0.91 (0.77–1.06)	1.04 (0.76–1.42)
Quartile 3	1.17 (0.87–1.57)	0.95 (0.82–1.11)	0.68 (0.52–0.88) ^**	0.99 (0.86–1.15)	0.91 (0.77–1.07)	0.92 (0.62–1.37)
Quartile 4	1.25 (0.93–1.67)	0.94 (0.80–1.11)	0.77 (0.61–0.97) ^*	1.13 (0.96–1.32)	0.93 (0.78–1.12)	0.82 (0.53–1.27)
P for trend	0.193	0.433	0.135	0.052	0.805	0.263
Model was adjusted as age, sex, race, education level, poverty, smoking, and alcohol use, body mass index, energy intake levels, physical activity, eGFR, uric acid, urinary creatinine, diabetes, and hypertension.
HDL-C, high-density lipoprotein cholesterol; TC, total cholesterol; TG, triglyceride; LDL-C, low-density lipoprotein cholesterol; Non-HDL-C, non-high-density lipoprotein cholesterol; Apo B, apolipoprotein B; CI, confidence interval; Ref., reference; ^* p < 0.05, ^ p < 0.01 and ^* p < 0.001.

Furthermore, the RCS logistic regression showed that log2-transformed thiocyanate was linearly associated with elevated TG, TC, LDL-C, non-HDL-C, and Apo B (all p for nonlinearity > 0.05), but nonlinearly associated with lowered HDL-C (p for nonlinearity < 0.001; inflection point [IP] = 1.622 mg/L) (Fig. 2). The dose–response relationships for perchlorate and nitrate with binary serum lipid variables are shown in Figures S2 and S3.

3.5 Associations of the mixture of thiocyanate, nitrate, and perchlorate with binary and continuous serum lipid variables

WQS regression was first used to assess the relationships between the mixture of thiocyanate, nitrate, and perchlorate and binary serum lipid variables (Table 4). The mixture was positively associated with elevated TG (OR = 1.05, 95% CI: 1.01, 1.09, p = 0.024), elevated TC (OR = 1.04, 95% CI: 1.01, 1.06, p = 0.007), elevated LDL-C (OR = 1.04, 95% CI: 1.01, 1.08, p = 0.018), lowered HDL-C (OR = 1.03, 95% CI: 1.01, 1.05, p = 0.007), and elevated non-HDL-C (OR = 1.04, 95% CI: 1.01, 1.07, p = 0.004) but there was no significant association with elevated Apo B. Regarding the continuous serum lipid variables, consistent findings were obtained for the association of the mixture with TG, TC, LDL-C, and non-HDL-C (though not with HDL-C), plus the mixture was significantly positively associated with Apo B (Table S5).

Table 4

WQS regression model to assess the association of the mixture of urinary perchlorate, nitrate, and thiocyanate with the prevalence of dyslipidemia in adults.
Outcomes	OR	95%CI	P value
Elevated TG (n = 7,236)	1.05	1.01–1.09	0.024
Elevated TC (n = 15,563)	1.04	1.01–1.06	0.007
Elevated LDL-C (n = 7,236)	1.04	1.01–1.08	0.018
Lowered HDL (n = 15,563)	1.03	1.01–1.05	0.007
Elevated Non-HDL-C (n = 15,563)	1.04	1.01–1.07	0.004
Elevated Apo B (n = 6,732)	1.02	0.96–1.08	0.574
Model was adjusted as age, sex, race, education level, poverty, smoking, alcohol use, body mass index, energy intake levels, physical activity, eGFR, uric acid, urinary creatinine, diabetes, and hypertension.
HDL-C, high-density lipoprotein cholesterol; TC, total cholesterol; TG, triglyceride; LDL-C, low-density lipoprotein cholesterol; Non-HDL-C, non-high-density lipoprotein cholesterol; Apo B, apolipoprotein B; CI, confidence interval.

This is the first study to investigate the associations of urinary thiocyanate, nitrate, and perchlorate concentrations with continuous and binary serum lipid variables (to explore associations with dyslipidemia) in a sample of 15,563 adults from the general population of the United States. Our two-tiered strategy first involved analyzing individual chemicals (thiocyanate, nitrate, and perchlorate) and then a mixture of the three. The latter analysis allowed us to determine the associations of co-exposure to thiocyanate, nitrate, and perchlorate with continuous and binary serum lipid variables. We discovered the following: (I) multivariate linear regression revealed that urinary thiocyanate was significantly positively associated with multiple continuous serum lipid variables (TG, TC, LDL-C, non-HDL-C, and Apo B) but not HDL-C; (II) multivariate logistic regression revealed that urinary thiocyanate was significantly positively associated with multiple binary serum lipid variables (elevated TG, TC, LDL-C, and non-HDL-C) but not Apo B or HDL-C, whereas urinary perchlorate was significantly negatively associated with elevated LDL-C; (III) multivariate RCS logistic regression revealed a linear dose–response relationship between the continuous urinary thiocyanate variable and multiple binary serum lipid variables (elevated TG, TC, LDL-C, non-HDL-C, and Apo B) and a nonlinear dose–response relationship with lowered HDL-C (IP = 1.622 mg/L); and (Ⅳ) WQS regression showed that the mixture of thiocyanate, nitrate, and perchlorate was significantly positively associated with all forms of dyslipidemia, except for elevated Apo B.

Environmental and dietary exposures to thiocyanate, nitrate, and perchlorate are ubiquitous, and the relationships between these three chemicals and human health has been widely reported. The effects of thiocyanate, nitrate, and perchlorate exposure on thyroid function in various populations have received widespread attention for decades (García Torres et al. 2022, King et al. 2022, Leung et al. 2014, Willemin &Lumen 2017). Observational studies have shown that thiocyanate, nitrate, and perchlorate are linked to higher cancer prevalence (Picetti et al. 2022, Said Abasse et al. 2022, Shiue 2015, Zhang et al. 2018), which is supported by several animal studies (Carvalho et al. 2021, Wang et al. 2022a, Wang et al. 2018). High urinary perchlorate was linked to a higher prevalence of diabetes and elevated levels of risk factors (fasting glucose, HbA1c, insulin, and homeostatic model assessment of insulin resistance) in a sample of 11,443 individuals (Liu et al. 2017). A cross-sectional study of adults in the United States showed that urinary nitrate was negatively linked to the prevalence of general and abdominal obesity, but urinary thiocyanate was positively associated with the prevalence of obesity (Zhu et al. 2019). In addition, there is strong evidence that nitrates (both pharmacological and dietary) increase CVD (heart failure (Ferguson et al. 2021), hypertension (Kapil et al. 2020), myocardial infarction (Jackson et al. 2017), and stroke (Jackson et al. 2017, Lundberg et al. 2008)) and metabolic syndrome (Kapil et al. 2020, Liu et al. 2020). However, there are few general population studies on the associations of thiocyanate, nitrate, and perchlorate exposure with continuous and binary serum lipid variables (the latter reflecting dyslipidemia). As several of the above studies suggest that long-term exposure to these three chemicals is a significant environmental risk factor for human health, they deserve further investigation.

Our analysis revealed a positive linear relationship between thiocyanate and dyslipidemia. Thiocyanate is the primary indirect marker of cyanide exposure (Bhandari et al. 2014). Myeloperoxidase (MPO)-catalyzed thiocyanate oxidation is an important endogenous source of cyanate (Bhandari et al. 2014). Cyanate has been shown to modify LDL and HDL through carbamylation (Holzer et al. 2011), which contributes to the development of AS, vascular endothelial dysfunction, and CVD (Verbrugge et al. 2015). In addition, cyanate exposure can affect liver function and lipid metabolism (Okafor et al. 2002, Sokołowska et al. 2011). Cyanate induces oxidative stress damage by inhibiting the NF-E2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) pathway, increases reactive oxygen species (ROS) levels, impairs liver function, and causes dyslipidemia (Hu et al. 2019). In a study of mice model, the cyanate group (compared to the control group) had significantly elevated liver function biomarkers (alanine aminotransferase [ALT], aspartate aminotransferase [AST], and alkaline phosphatase [ALP]), TC, and LDL-C and significantly decreased HDL-C (Hu et al. 2019). It is believed that oxidative stress may be a significant mechanism involved in lipid metabolism (Chen et al. 2003, Tangvarasittichai 2015), and impaired antioxidant capacity can accelerate the development of hyperlipidemia. The liver's primary physiological function is to metabolize glucose and lipids, and it plays a crucial role in the regulation of insulin sensitivity, inflammatory responses, and oxidative stress (Alfaradhi et al. 2014). Moreover, thiocyanate exposure typically induces a hyperinflammatory response (White et al. 2018, Whitehouse &Jones 2009, Zhu et al. 2021). Population studies have shown that thiocyanate exposure induces allergic inflammation and is associated with allergy-related symptoms (Zhu et al. 2021). In addition, elevated thiocyanate in smokers has been associated with impaired innate immune responses (White et al. 2018). In an animal study, thiocyanate supplementation increased inflammatory responses to multiple factors that cause arthritis/fibrotic inflammation (Whitehouse &Jones 2009). Increased inflammatory responses are thought to be associated with lipid metabolism (Esteve et al. 2005, van Diepen et al. 2013), which provides insight into the potential causes of dyslipidemia associated with thiocyanate exposure. Nevertheless, further research is required to investigate the pathways between thiocyanate exposure and dyslipidemia.

Our analysis also revealed that urinary perchlorate was negatively associated with elevated LDL-C, but not other dyslipidemia indicators, which is interesting and somewhat unexpected. This is because in a recent animal experiment, mice fed a high-fat diet and exposed to perchlorate exhibited no significant changes in LDL-C, though HDL-C was significantly increased (Wang et al. 2022c). Additionally, a study of zebrafish found that perchlorate exposure (relative to control treatment) failed to alter liver or systemic lipid accumulation (Minicozzi et al. 2021). The exact mechanism by which perchlorate affected lipid metabolism in our study remains to be determined. In addition, consistent with previous findings (DesOrmeaux et al. 2021, Khalifi et al. 2015), we found that creatinine-corrected nitrate was negatively associated with dyslipidemia (elevated LDL-C and non-HDL-C).

Our study also has some limitations. First, the causality regarding the associations of urinary thiocyanate, nitrate, and perchlorate with dyslipidemia were not explored because the temporal relationship between these factors could not be determined. Second, missing serum lipid data, especially TG, LDL-C, and Apo B data, reduced the sample size and decreased the statistical power. Third, although we adjusted our models for many confounders, residual confounders may affect the results. Fourth, the NHANES data on thiocyanate, nitrate, and perchlorate were collected from a single urine spot sample per participant, which may not accurately reflect long-term exposure status.

Our findings demonstrate that urinary thiocyanate is positively linearly associated with dyslipidemia (elevated TG, TC, LDL-C, and non-HDL-C) in the general adult population of the United States, whereas urinary perchlorate is negatively associated with elevated LDL-C. Furthermore, exposure to a mixture of urinary thiocyanate, nitrate, and perchlorate was positively associated with a higher prevalence of all types of dyslipidemia except for elevated Apo B. For validation and expansion of our findings, prospective and mechanistic research is necessary.

Acknowledgments

We appreciate the people who contributed to the NHANES data we studied.

Funding

No specific funding was received for this work.

Authors Contributions

Mengsha Shi: Conceptualization, Methodology, Formal analysis, Writing-original draft, Visualization. Xu Zhu: Conceptualization, Methodology, Software, Writing-original draft, Supervision. Iokfai Cheang: Formal analysis. Qingqing Zhu: Formal analysis. Qixin Guo: Writing-review and editing. Shengen Liao: Project administration, Writing-review and editing. Rongrong Gao: Conceptualization, Supervision. Xinli Li: Conceptualization, Methodology, Project administration, Supervision.

Ethics approval and consent to participant

All participants provided written informed consent and study procedures were approved by the National Center for Health Statistics Research Ethics Review Board.

Consent to publish

The manuscript is approved by all authors for publication.

Competing interests

The authors declare no or competing interests.

Availability of data and materials

Publicly available datasets were analyzed in this study. This data can be found here: https://www.cdc.gov/nchs/nhanes/.

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Associations of thiocyanate, nitrate, and perchlorate exposure with dyslipidemia: a cross-sectional, population-based analysis

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Abstract

Figures

1. Introduction

2. Methods

2.1 Study population

2.2 Assessment of urinary thiocyanate, nitrate, and perchlorate

2.3 Assessment of serum lipid variables

2.4 Covariates

2.5 Statistical analysis

3. Results

3.1 Participant characteristics

3.2 Distributions and correlations of thiocyanate, nitrate, and perchlorate

3.3 Associations of thiocyanate, nitrate, and perchlorate with continuous serum lipid variables

3.4 Associations of thiocyanate, nitrate, and perchlorate with binary serum lipid variables

4. Discussion

5. Conclusions

Declarations

References

Supplementary Files

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