Hair mercury isotopes, a noninvasive biomarker for dietary methylmercury exposure and biological uptake

Abstract

Background. Fish and rice are the main dietary sources of methylmercury (MeHg); however, rice does not contain the same beneficial nutrients as fish, and these differences can impact the observed health effects of MeHg. Hence, it is important to validate a biomarker, which can distinguish among dietary MeHg sources. Methods. Mercury (Hg) stable isotopes were analyzed in hair samples from peripartum mothers in China (n = 265). Associations between mass dependent fractionation (MDF) (δ²⁰²Hg) and mass independent fractionation (MIF) (Δ¹⁹⁹Hg) (dependent variables) and dietary MeHg intake (independent variable) were investigated using multivariable regression models. Results. In adjusted models, hair Δ¹⁹⁹Hg was positively correlated with serum omega-3 fatty acids (a biomarker for fish consumption) and negatively correlated with maternal rice MeHg intake, indicating MIF recorded in hair can be used to distinguish MeHg intake predominantly from fish versus rice. Conversely, in adjusted models, hair δ²⁰²Hg was not correlated with measures of dietary measures of MeHg intake. Instead, hair δ²⁰²Hg was strongly, negatively correlated with hair Hg, which explained 27–29% of the variability in hair δ²⁰²Hg. Conclusions. Our results indicated that hair Δ¹⁹⁹Hg can be used to distinguish MeHg intake from fish versus rice. Results also suggested that lighter isotopes were preferentially accumulated in hair, potentially reflecting Hg binding to thiols (i.e., cysteine); however, more research is needed to elucidate this hypothesis. Broader impacts include 1) validation of a non-invasive biomarker to distinguish MeHg intake from rice versus fish, and 2) the potential to use Hg isotopes to investigate Hg binding in tissues.

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Environmental significance

There is evidence that hair mercury (Hg) isotopes, specifically mass independent fractionation (MIF), can be used as a conservative tracer for dietary methylmercury (MeHg) intake; however, prior studies had small sample sizes (n = 5–45) and most studies focused on fish consumers. To the best of our knowledge, this is the first large-scale study to investigate the utility of hair Hg isotopes as non-invasive biomarkers of dietary MeHg intake (n = 265 peripartum mothers). Most mothers ingested rice daily while a majority of mothers also ingested some fish. Using a robust modeling approach (multivariable regression), our results support the notion that MIF can distinguish MeHg intake primarily from rice versus fish, providing a potentially valuable non-invasive MeHg exposure biomarker for health effects studies.

Introduction

Methylmercury (MeHg) is a potent neurotoxicant, and the developing fetus is at highest risk.¹ Fish and rice are considered the main dietary sources of MeHg;^2,3 however, measurement of MeHg [or total mercury (THg)] in biomarkers (e.g., hair, blood, urine, and stool) does not discern the dietary sources of MeHg. To investigate the human health risks due to MeHg exposure from ingestion of rice versus fish, it is important to validate a biomarker, especially a non-invasive biomarker, which can distinguish between the two dietary MeHg sources as they have different co-occurring nutrients which, in turn, may differentially confound or modify associations.³

Mercury (Hg) has seven stable isotopes, which can be used to trace sources and geochemical pathways of Hg in the environment.⁴ All Hg isotopes undergo mass-dependent fractionation (MDF, represented by δ²⁰²Hg), which is produced during biological, chemical, and physical transformations of Hg.⁴ In addition, Hg is one of the few elements that undergoes mass-independent fractionation (MIF), which is a deviation from the predicted MDF for an isotope.⁴ Hg-MIF of odd isotopes (represented by Δ¹⁹⁹Hg and Δ²⁰¹Hg) mainly occurs during photochemical processes,^5,6 while Hg-MIF of even isotopes (represented by Δ²⁰⁰Hg and Δ²⁰⁴Hg) has been reported for gaseous Hg(0) processes in the atmosphere.^7,8

To date, just 10 studies have reported Hg isotopes in human hair, and all were limited to small sample sizes (n = 5–45) (Table S1†).^9–18 Two main findings have been reported. First, unlike MDF, the MIF induced by photochemical reactions was conserved during trophic transfer and was used to track dietary MeHg intake from seafood and rice.^10–16 However, some discordance (i.e., lack of association) was noted between Δ¹⁹⁹Hg and estimates of fish/rice consumption in our prior study among 21 mothers,¹⁵ suggesting other factors contributed to these associations (discussed below). Second, higher hair δ²⁰²Hg values relative to the dietary source (∼2‰) were hypothesized to reflect MeHg metabolism (i.e., demethylation) by gut microbiota.^13,19 Given that MeHg's isotopic composition (specifically MDF) is altered during metabolism, other factors that influence MeHg metabolism may also impact the MDF and MIF isotopic composition of hair; however, these associations have not been investigated in prior studies. For example, fruit and fiber intake were both associated with lower uptake of MeHg in hair and tissues,^20,21 which potentially reflected more efficient metabolism and excretion of MeHg. Factors associated with altered structure or function of the gut microbiome, including body mass index (BMI)²² and dietary omega-3 fatty acid intake,²³ may also impact MeHg metabolism. Higher BMI, itself, was also associated with lower blood Hg in adults suggesting potential BMI-related differences in metabolism.²⁴ Thus, dietary fiber/fruit intake and BMI may be important covariates to consider when assessing the relationship of dietary MeHg intake with MDF, while seafood intake (a rich source of omega-3 fatty acids)²⁵ may influence both MDF and MIF.

We leveraged our birth cohort study in rural China, including 265 peripartum mothers,^26–28 to determine the utility of hair Hg isotopes as non-invasive biomarkers for dietary MeHg intake and metabolism, the first large-scale study to date.

Materials and methods

Daxin birth cohort study

Between May 2013–March 2014, 398 peripartum mothers were enrolled at the Maternal and Child Health Hospital in Daxin county, Guangxi province, China (Supporting Information, detailed methods). Mothers provided written informed consent prior to enrollment in the study. Study protocols were reviewed and approved by the Institutional Review Boards at the University of South Carolina (USA), Xin Hua Hospital (China), and Oregon State University (USA). This study was performed in compliance with all relevant guidelines.

Rice/fish MeHg intake

While in the hospital, mothers completed a modified semi-quantitative 102-item food frequency questionnaire (FFQ), reflecting food intake during the third trimester. The FFQ included ingestion of rice, seven categories of fish/shellfish (freshwater fish, ocean fish, shrimp, eel, snails, crab, and other shellfish) (hereafter “fish”), and other foods.²⁹ Data from the FFQ were used to calculate rice MeHg intake (μg per day), fish MeHg intake (μg per day), maternal energy intake (kcal), and the proportion (%) of calories from protein, carbohydrates, and fat (ESI,† detailed methods).

Biomarker collection

While mothers were in the hospital, a maternal hair sample (∼50 strands) was collected for analysis of Hg. With the proximal end secured, it was possible to analyze hair segments that corresponded to exposures occurring during each trimester of pregnancy, based on the growth rate of hair for Asian women.³⁰ Moreover, hair is not subject to metabolic properties once it emerges from the scalp. At the same time, a maternal blood sample was collected for analysis of polyunsaturated fatty acids (with serum separated by centrifugation) (ESI,† detailed methods).

Hair Hg isotopes

We previously analyzed hair Hg isotopes for 21 mothers from this cohort.¹⁵ In the present study, Hg isotopes were analyzed in 244 additional maternal hair samples (n = 265/398, 67%). For most mothers, maternal hair samples corresponded to exposures during the second trimester (n = 252/265, 95%). Due to limited mass of second trimester hair, Hg isotopes for 13 mothers (5%) were analyzed in hair samples corresponding to exposures in the second trimester plus the first or third trimesters. In addition, 15 hair samples were randomly selected for analysis of isotopes in the third trimester to compare with results for the second trimester.

Hg isotopes were analyzed at the U.S. Geological Survey Mercury Research Laboratory (Madison, WI), as previously described.^31,32 Isotope ratios were measured using a Neptune Plus multicollector-inductively coupled plasma-mass spectrometer (MC-ICP-MS, Thermo Finnigan Neptune) (ESI,† detailed methods).^31,32 MDF (represented by δ²⁰²Hg) was calculated using eqn (1). MIF was expressed as Δ^xxxHg (represented by Δ¹⁹⁹Hg and Δ²⁰¹Hg), which was defined as the difference between the measured δ^xxxHg value and the value predicted based on the kinetic MDF law derived from transition state theory (i.e., δ²⁰²Hg value multiplied by a constant) (eqn (2) and (3)).^4,33

δ²⁰²Hg (‰) = [(δ²⁰²Hg/δ¹⁹⁸Hg)_sample/(δ²⁰²Hg/δ¹⁹⁸Hg)_{NIST 3133} − 1] × 1000 (1)

Δ¹⁹⁹Hg = δ¹⁹⁹Hg − (δ²⁰²Hg × 0.2520) (2)

Δ²⁰¹Hg = δ²⁰¹Hg − (δ²⁰²Hg × 0.7520) (3)

A secondary standard (UM-Almadén) was run every five samples to ensure accuracy and precision of measurements. UM-Almadén and IAEA-086 isotope values agreed with established values (Table S2; ESI, and Dataset S1†).

THg and MeHg analyses

For THg and MeHg analyses, refer to detailed methods in ESI.† At the U.S. Geological Survey Mercury Research Laboratory, hair THg concentrations were analyzed to ensure proper concentration matching during isotope analysis, using U.S. Environmental Protection Agency (EPA) Method 1631.³⁴ Hair MeHg concentrations corresponding to the third trimester and rice MeHg concentrations were analyzed at the University of South Carolina using EPA Method 1630 (Brooks Rand Model III, Seattle, WA, USA).³⁵ Fish tissue THg concentrations were analyzed at the Beijing Lumex Analytical Co. Ltd., China, using EPA Method 7473.³⁶ All THg and MeHg analyses met quality control and quality assurance criteria (Table S2†). The average recoveries for standard reference materials and matrix spikes ranged from 78–98%, and the average relative standard deviation for replicate analyses ranged from 4.2–8.4% (Table S2†).

Statistics

Bivariate analyses were conducted using Wilcoxon rank sum test, Kruskal–Wallis test, Chi-squared test, Fisher's exact test, and Spearman's rho. To compare the second and third trimesters, a 2-sided paired t-test was used. The ratio between Δ¹⁹⁹Hg and Δ²⁰¹Hg represents photochemical degradation of Hg(II) and MeHg, and was assessed using simple linear regression, as previously described.⁴

Multivariable regression models were used to investigate associations between hair MDF (δ²⁰²Hg) and hair MIF (Δ¹⁹⁹Hg) (dependent variables) and dietary MeHg intake (independent variable). Four potential estimates of dietary MeHg intake were identified to evaluate whether the MeHg source (rice or fish) impacted the hair Hg isotopic composition:

Model A: weekly fish ingestion (3 categories) and daily rice ingestion (yes/no); Model B: %MeHg intake from rice; Model C: log₁₀ rice MeHg intake (μg per day) and log₁₀ fish MeHg intake (μg per day); and Model D: log₁₀ serum omega-3 fatty acids (mg mL⁻¹) and log₁₀ serum n-6 fatty acids (mg mL⁻¹).

Each isotopic endpoint (δ²⁰²Hg or Δ¹⁹⁹Hg) was examined in relation to these four sets of variables (ESI,† detailed methods). Prior studies have reported a positive association between Δ¹⁹⁹Hg and weekly fish ingestion (Model A), and an inverse association between Δ¹⁹⁹Hg and %MeHg intake from rice (Model B).^10,15 Percent MeHg intake from rice was derived as the ratio of rice MeHg intake to the sum of rice and fish MeHg intake, which was used in Model C. Fish tissue is a rich source of omega-3 fatty acids, which compete with omega-6 fatty acids for the same enzymes in biosynthetic pathways;²⁵ thus both were included in Model D.

We fit both unadjusted and covariate-adjusted models. The latter were adjusted for the same set of covariates, which were selected based on inclusion in previous studies investigating dietary MeHg exposure and metabolism.^{19,20,23,27,28} Additional covariates included maternal age at study enrollment (years), maternal pre-pregnancy BMI (3 categories: underweight, normal weight, and overweight/obese), log₁₀ maternal energy intake (kcal), maternal proportion of calories (%) from protein, log₁₀ maternal hair THg, and whether one or both parents was a farmer (yes/no). Energy intake (kcal) served as a proxy for fruit intake (servings per day) and fiber intake (g per day) (Spearman's rho: 0.52 and 0.85, respectively). A log₁₀-transformation was applied to continuous variables that were skewed right to improve normality of the residuals. Missing data on covariates were imputed as the mean from multiple imputation based on the multivariate normal distribution,³⁷ conditional on parental and child characteristics, and maternal biomarker concentrations, as previously described.^27,28 Cook's distance was used to assess influential observations, and assumptions for model residuals were checked (no evidence of non-linearity, constant variance, normal distribution).

As sensitivity analyses, we investigated regression models: (1) excluding mothers with imputed data; (2) including hair samples corresponding to exposures during the second trimester only; (3) excluding 21 hair samples previously measured;¹⁵ and (4) excluding households where one or both parents were farmers because parental occupation (farmer/non-farmer) correlated with rice/fish ingestion (Table S3†). Lastly, as a sensitivity analysis, associations between hair Hg isotopes and hair MeHg concentrations were investigated in a subset of 15 mothers for which hair MeHg concentrations were previously analyzed.²⁶

An alpha-level of 0.05 was selected as a guide for significance. Analyses were performed using Stata (Version 17.0, College Station, TX, USA), and the R-platform (Version 4.3.0, 21 April 2023).

Results

Maternal characteristics

Maternal age averaged (±1 standard deviation) 28 ± 5.7 years (range: 17–45 years), 78% of mothers did not complete high school, and 87% of mothers identified as Zhuang ethnicity (Table S4†). Among participating mothers, fewer parents were farmers (76%) compared to non-participating mothers (85%) (Chi-squared test, p = 0.02). Moreover, the total energy intake (kcal) and the %calories from protein were higher among participating mothers, compared to non-participating mothers (Wilcoxon rank sum test, p = 0.014 and p = 0.0007, respectively) (Table S5†). Lastly, there were no participating mothers who smoked during pregnancy, whereas five non-participating mothers smoked (Chi-squared test, p = 0.004) (Table S4†).

Rice and fish MeHg intake

Rice ingestion was the primary dietary source of MeHg; the median %MeHg intake from rice was 82%, while the median %MeHg intake from fish was 18% (Table S5†). Most mothers (82%) ingested rice daily, while 42% rarely or never ingested fish (Table S4†). Mothers ingested on average 1.8 servings per day of rice and only 0.93 meals of fish weekly. The median MeHg intake from rice (0.43 μg per day) was 2.5 times higher than the median MeHg intake from fish (0.17 μg per day) (Table S5†).

Hair THg

Hair samples corresponded to exposures mainly during the second trimester; the median hair THg concentration was 0.47 μg g⁻¹ (range: 0.13, 1.8 μg g⁻¹) (Tables S1 and S5†).

Hair Hg isotopic composition

The median values (range) for hair δ²⁰²Hg, Δ¹⁹⁹Hg, and Δ²⁰¹Hg were 0.44‰ (range: −0.89‰, 1.8‰), 0.13‰ (range: −0.15‰, 0.66‰), and 0.08‰ (range: −0.18‰, 0.47‰), respectively (Table S1†). The range between minimum/maximum values for hair δ²⁰²Hg was 2.69‰, while the ranges for hair Δ¹⁹⁹Hg and Δ²⁰¹Hg were narrower (0.81‰ and 0.65‰, respectively). The photochemical slope between Δ¹⁹⁹Hg and Δ²⁰¹Hg in hair samples was 1.12, which was lower than the slope associated with previous literature studies (slope = 1.18) (Fig. 1b) but similar to the slope associated with rice samples (slope = 1.11).¹⁵ Hair Δ¹⁹⁹Hg and δ²⁰²Hg (for this study) were slightly positively correlated (Spearman's rho: 0.25) (Fig. 1c).

Fig. 1 Comparison of hair mercury (Hg) isotopes, including (a) Δ¹⁹⁹Hg versus δ²⁰²Hg (all studies), (b) Δ¹⁹⁹Hg versus Δ²⁰¹Hg (all studies), (c) Δ¹⁹⁹Hg versus δ²⁰²Hg (this study only), and (d) Δ¹⁹⁹Hg versus Δ²⁰¹Hg (this study only). Representative values for 2 standard deviations of analytical uncertainty measured for this study (c and d) were 0.08 (δ²⁰²Hg), 0.05 (Δ¹⁹⁹Hg) and 0.05 (Δ²⁰¹Hg). For a and b, studies were ranked from highest to lowest median hair Δ¹⁹⁹Hg values (Table S1†).

Compared to nearly all other study populations (11 of 14 populations) in which hair Hg isotopes were reported (Fig. 1 and Table S1†),^{9–14,16–18} the median values for δ²⁰²Hg, Δ¹⁹⁹Hg, and Δ²⁰¹Hg from the present study were lower. There were just three exceptions; lower median values for one or more hair Hg isotopes were reported in Guizhou province, China^10,14 and among Ghanaian artisanal gold miners using Hg amalgamation,¹⁷ compared to the present study.

Hair Hg isotopes and rice/fish consumption

For Models A–D, associations were investigated between hair Hg isotopes and rice/fish consumption (Tables 1–4). In Models A and B, in the unadjusted models, hair Δ¹⁹⁹Hg was higher for mothers who consumed at least two fish meals per week, compared to mothers who did not ingest fish (beta: 0.082‰, 95% CI: 0.024‰, 0.14‰), and negatively associated with %MeHg intake from rice (beta: −0.00060‰, 95% CI: −0.0011‰, −0.00011‰). However, these associations were attenuated after covariate adjustment (Tables 1 and 2).

Table 1 Multivariable regression results relating maternal hair isotopes with fish weekly servings and daily rice ingestion (Model A) (n = 265 mothers)^a

	Hair Δ^199Hg (‰)			Hair δ^202Hg (‰)
	Beta	(95% confidence interval)	p-Value	Beta	(95% confidence interval)	p-Value
a *p < 0.05 **p ≤ 0.01 ***p ≤ 0.001 p-value is for the Beta coefficient. BMI (body mass index), Hg (mercury), THg (total mercury).
Unadjusted
Fish weekly servings
Never or rarely	(Referent)			(Referent)
0 < servings per weekly ≤ 2	0.018	(-0.017, 0.054)	0.31	−0.042	(-0.19, 0.11)	0.58
≥ 2 servings per weekly	0.082	(0.024, 0.14)	0.005**	−0.0015	(-0.24, 0.24)	0.99
Daily rice ingestion (yes)	0.00052	(-0.048, 0.049)	0.98	−0.034	(-0.24, 0.17)	0.74
Adjusted
Fish weekly servings
Never or rarely	(Referent)			(Referent)
0 < servings per weekly ≤ 2	0.0052	(-0.031, 0.042)	0.78	−0.031	(-0.16, 0.10)	0.65
≥ 2 servings per weekly	0.050	(-0.016, 0.12)	0.14	0.079	(-0.16, 0.32)	0.52
Daily rice ingestion (yes)	−0.0015	(-0.062, 0.059)	0.96	−0.0013	(-0.22, 0.22)	0.99
log 10 hair THg (μg g ^−1 )	−0.11	(−0.19, −0.032)	0.006**	−1.7	(−1.8, −1.1)	<0.001***
Maternal age (years)	0.00034	(−0.0026, 0.0033)	0.82	0.016	(0.0047, 0.026)	0.005**
Pre-pregnancy BMI (kg m^− ^2 )
Underweight	(Referent)			(Referent)
Normal weight	0.0068	(-0.033, 0.047)	0.74	0.052	(-0.094, 0.20)	0.49
Overweight or obese	0.0042	(-0.048, 0.056)	0.87	0.12	(-0.073, 0.31)	0.23
Mother or father is a farmer (yes)	−0.054	(−0.095, −0.013)	0.01**	−0.097	(-0.25, 0.053)	0.21
log 10 maternal energy intake (kcal)	0.0039	(-0.15, 0.14)	0.96	−0.042	(-0.58, 0.49)	0.88
Maternal %calories from protein	0.0034	(-0.0045, 0.011)	0.40	−0.014	(-0.043, 0.014)	0.33

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Table 2 Multivariable regression results relating maternal hair isotopes with %methylmercury intake from rice (Model B) (n = 263 mothers)^a,b

	Hair Δ^199Hg (‰)			Hair δ^202Hg (‰)
	Beta	(95% confidence interval)	p-Value	Beta	(95% confidence interval)	p-Value
a *p < 0.05 **p ≤ 0.01 ***p < 0.001 p-value is for the Beta coefficient. BMI (body mass index), Hg (mercury), THg (total mercury). b Two mothers did not eat rice or fish, reducing the sample size from 265 to 263.
Unadjusted
% MeHg intake from rice	−0.00060	(−0.0011, −0.00011)	0.02*	0.00035	(−0.0017, 0.0025)	0.74
Adjusted
% MeHg intake from rice	−0.00031	(−0.00086, 0.00023)	0.26	−0.00019	(−0.0022, 0.0018)	0.86
log 10 hair THg (μg g ^−1 )	−0.12	(−0.19, −0.039)	0.003**	−1.4	(−1.7, −1.2)	<0.001***
Maternal age (years)	0.00033	(-0.0025, 0.0032)	0.82	0.016	(0.0050, 0.026)	0.004**
Pre-pregnancy BMI (kg m^− ^2 )
Underweight	(Referent)
Normal weight	0.0013	(−0.037, 0.040)	0.95	0.046	(−0.099, 0.19)	0.54
Overweight or obese	0.0038	(−0.047, 0.055)	0.88	0.12	(−0.073, 0.31)	0.23
Mother or father is a farmer (yes)	−0.058	(−0.098, −0.018)	0.004**	−0.092	(−0.24, 0.056)	0.22
log 10 maternal energy intake (kcal)	0.023	(−0.091, 0.14)	0.69	−0.091	(−0.51, 0.33)	0.67
Maternal %calories from protein	0.0031	(−0.0045, 0.011)	0.42	−0.0081	(−0.036, 0.020)	0.57

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Table 3 Multivariable regression results relating maternal hair isotopes with rice methylmercury intake and fish methylmercury intake (Model C) (n = 265 mothers)^a

	Hair Δ^199Hg (‰)			Hair δ^202Hg (‰)
	Beta	(95% confidence interval)	p-Value	Beta	(95% confidence interval)	p-Value
a *p < 0.05 **p < 0.01 ***p < 0.001 p-value is for the Beta coefficient. BMI (body mass index), Hg (mercury), THg (total mercury).
Unadjusted
log 10 rice MeHg intake (μg per day)	−0.031	(-0.063, 0.0024)	0.052	−0.15	(−0.28, −0.019)	0.03*
log 10 fish MeHg intake (μg per day)	0.025	(0.0068, 0.043)	0.007**	−0.035	(−0.11, 0.040)	0.36
Adjusted
log 10 rice MeHg intake (μg per day)	−0.038	(−0.075, −0.00098)	0.04*	−0.096	(−0.23, 0.040)	0.17
log 10 fish MeHg intake (μg per day)	0.014	(−0.0066, 0.034)	0.19	−0.014	(−0.088, 0.061)	0.72
log 10 hair THg (μg g ^−1 )	−0.10	(−0.18, −0.020)	0.01*	−1.4	(−1.7, −1.1)	<0.001***
Maternal age (years)	0.00021	(−0.0027, 0.0031)	0.89	0.015	(0.0046, 0.026)	0.005**
Pre-pregnancy BMI (kg m^− ^2 )
Underweight	(Referent)
Normal weight	0.0063	(−0.033, 0.046)	0.75	0.048	(−0.096, 0.19)	0.51
Overweight or obese	0.0072	(−0.045, 0.059)	0.78	0.12	(−0.067, 0.31)	0.20
Mother or father is a farmer (yes)	−0.057	(−0.098, −0.017)	0.006**	−0.11	(−0.26, 0.038)	0.15
log 10 maternal energy intake (kcal)	0.061	(−0.074, 0.20)	0.38	0.13	(−0.36, 0.63)	0.60
Maternal %calories from protein	0.0017	(−0.0060, 0.0094)	0.67	−0.015	(−0.043, 0.014)	0.31

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Table 4 Multivariable regression results relating maternal hair isotopes with serum omega-3 fatty acids and serum omega-6 fatty acids (Model D) (n = 265 mothers)^a

	Hair Δ^199Hg (‰)			Hair δ^202Hg (‰)
	Beta	(95% confidence interval)	p-Value	Beta	(95% confidence interval)	p-Value
a *p < 0.05 **p < 0.01 ***p ≤ 0.001 p-value is for the Beta coefficient. BMI (body mass index), Hg (mercury), N-3 fatty acids (docosahexaenoic acid, eicosapentaenoic acid, and alpha-linolenic acid), N-6 fatty acids (linoleic acid and arachidonic acid), total mercury (THg).
Unadjusted
log 10 serum N-3 fatty acids (mg mL ^−1 )	0.25	(0.13, 0.38)	<0.001***	−0.11	(−0.66, 0.44)	0.70
log 10 serum N-6 fatty acids (mg mL ^−1 )	0.11	(-0.19, 0.41)	0.49	0.12	(−1.2, 1.4)	0.86
Adjusted
log 10 serum N-3 fatty acids (mg mL ^−1 )	0.27	(0.14, 0.39)	<0.001***	0.17	(−0.30, 0.64)	0.47
log 10 serum N-6 fatty acids (mg mL ^−1 )	−0.0059	(-0.29, 0.30)	0.97	−0.49	(−1.6, 0.64)	0.40
log 10 hair THg (μg g ^−1 )	−0.13	(−0.20, −0.052)	0.001***	−1.5	(−1.7, −1.2)	<0.001***
Maternal age (years)	0.00040	(−0.0024, 0.0032)	0.78	0.016	(0.0056, 0.027)	0.003**
Pre-pregnancy BMI (kg m^− ^2 )
Underweight	(Referent)
Normal weight	−0.0034	(-0.042, 0.035)	0.86	0.043	(−0.10, 0.19)	0.56
Overweight or obese	0.0025	(-0.053, 0.048)	0.92	0.11	(−0.078, 0.30)	0.25
Mother or father is a farmer (yes)	−0.046	(−0.086, −0.0068)	0.02*	−0.10	(−0.25, 0.048)	0.18
log 10 maternal energy intake (kcal)	−0.0020	(-0.11, 0.11)	0.97	−0.077	(−0.49, 0.34)	0.72
Maternal %calories from protein	0.0049	(−0.0019, 0.012)	0.16	−0.0094	(−0.035, 0.016)	0.47

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In Models C and D, in the adjusted models, hair Δ¹⁹⁹Hg was negatively associated with rice MeHg intake (beta: −0.038‰, 95% CI: −0.075‰, −0.00098‰) (Table 3), and positively associated with serum omega-3 fatty acids (beta: 0.27‰, 95% CI: 0.14‰, 0.39‰) (Table 4), respectively. Moreover, in all four models, hair Δ¹⁹⁹Hg was negatively associated with hair THg (Fig. 2b), and whether one or both parents were farmers (Tables 1–4). The latter association likely reflected lower fish consumption among farmers, compared to non-farmers (Table S3†).

Fig. 2 Partial regression plots from the fully adjusted regression models relating hair mercury (Hg) isotopes versus log₁₀ hair total mercury (THg) for a) hair δ²⁰²Hg, and (b) hair Δ¹⁹⁹Hg. These results are for Model D (Table 4); similar results were observed for Models A–C (Tables 1–3) (n = 265 mothers). For Model D, models were adjusted for log₁₀ serum n-3 fatty acids (mg mL⁻¹), log₁₀ serum n-6 fatty acids (mg mL⁻¹), maternal age (years), pre-pregnancy body mass index (kg m⁻²) (3 categories), whether at least one parent was a farmer (yes/no), log₁₀ maternal energy intake (kcal), and %calories from protein.

In the unadjusted model (Model C), hair δ²⁰²Hg was negatively associated with rice MeHg intake (beta: −0.15‰, 95% CI: −0.28‰, −0.019‰) (Table 3). However, in the adjusted models (Models A–D), hair δ²⁰²Hg was not associated with estimates for rice or fish ingestion (Tables 1–4). In all four models, hair δ²⁰²Hg was strongly, negatively associated with hair THg (Fig. 2a), and positively associated with maternal age (Tables 1–4).

Sensitivity analyses

Among non-farmers (n = 62) (Tables S6–S9†), hair Δ¹⁹⁹Hg was positively associated with higher omega-3 fatty acids (Model D), as in the main analyses (Beta in adjusted model: 0.51‰, 95% CI: 0.24‰, 0.79‰) (Table S9†). However, the direction of association between hair Δ¹⁹⁹Hg and rice MeHg intake (Model C) in non-farmers was positive, as compared to a negative association in the main analysis. Consistent with the small sample size, it was also imprecise and included the null (beta in adjusted model: 0.039‰, 95% CI: −0.082‰, 0.16‰) (Table S8†).

Regression models were also re-evaluated excluding those participants with imputed data (Tables S10–S13†), including those participants with hair Hg isotopes corresponding to exposures only during the second trimester (Tables S14–S17†), and excluding 21 maternal hair samples previously analyzed (Tables S18–S21†).¹⁵ Similar results were observed as in the main analyses, including associations between hair Δ¹⁹⁹Hg and serum omega-3 fatty acids (Tables S13, S17, and S21†), and between hair δ²⁰²Hg and hair THg and maternal age (Tables S10–21†). Additionally, the same direction of association was observed between hair Δ¹⁹⁹Hg and hair THg and whether one or both parents were farmers (Tables S10–S21†). Lastly, the same direction of association was observed between hair Δ¹⁹⁹Hg and rice MeHg intake (Model C) (Tables S12, S16, and S20†), as in the main analyses.

For the subset of 15 mothers with paired hair measurements reflecting second and third trimester exposures, positive correlations were observed for hair δ²⁰²Hg and hair Δ¹⁹⁹Hg (Spearman's rho: 0.84 and 0.56, respectively) (Fig. S1†). Hair δ²⁰²Hg values corresponding to the third trimester were lower (median hair δ²⁰²Hg: 0.18‰), compared to hair δ²⁰²Hg corresponding to second trimester exposures (median hair δ²⁰²Hg: 0.43‰) (paired t-test, p = 0.0003) (Fig. 3 and S1†). Conversely, no differences were observed for Δ¹⁹⁹Hg values between the second and third trimester exposure periods (paired t-test, p = 0.11) (Fig. 3 and S1†).

Fig. 3 Spaghetti plots comparing mercury (Hg) isotopes measured in paired maternal hair samples corresponding to exposures during the second and third trimesters for a) hair δ²⁰²Hg, and b) hair Δ¹⁹⁹Hg (n = 15 mothers).

Discussion

Hair MIF (Δ¹⁹⁹Hg and Δ²⁰¹Hg) has been used as a tracer for fish ingestion.^{10–13,15,16} Unlike MDF (δ²⁰²Hg), no significant MIF occurs between seafood ingestion and deposition in human hair,¹³ thus enabling MIF to act as a well-conserved tracer of seafood MeHg. Hair Δ¹⁹⁹Hg values are also used to distinguish between seafood and rice ingestion, because Δ¹⁹⁹Hg values are higher for fish compared to rice.^10,14,15,38 In the present study, hair Δ¹⁹⁹Hg was negatively associated with daily MeHg intake from rice (Model C) and positively associated with serum omega-3 fatty acids (Model D), indicating that MIF (hair Δ¹⁹⁹Hg) was able to distinguish between MeHg exposure from rice versus fish.

In contrast to previously reported results,^10,15 in the adjusted models, hair Δ¹⁹⁹Hg was not associated with the number of fish meals ingested weekly, nor with %MeHg intake from rice (Models A and B, respectively). The three estimates used in Models A–C were derived from the mother's self-reported FFQ, and (for two of the estimates) from analyses of MeHg (in rice) and THg (in fish). Several factors potentially contributed to more uncertainty in the FFQ estimate for fish ingestion (which was used in Models A and B), compared to rice ingestion. First, recall bias is often higher for foods ingested seasonally or infrequently.³⁹ In this population, 82% of the mothers ingested rice daily and 42% of the mothers rarely or never ingested fish; therefore, recall bias for fish consumption was likely higher, compared to rice ingestion. Second, MeHg concentrations were measured in rice samples brought from each participant's home, whereas THg concentrations in ocean fish and shellfish were estimated from a literature review (ESI,† detailed methods).²⁶ Lastly, each mother estimated her rice ingestion rate (g per serving) by selecting bowls with known quantities of rice, whereas fish serving sizes were assumed to be the same for all mothers (ESI,† detailed methods). Although all three measures were derived in part from the FFQ, the estimate for MeHg intake from rice potentially had less measurement error compared to the estimate for MeHg intake from fish.

In the adjusted models, hair Δ¹⁹⁹Hg was strongly, positively associated with serum omega-3 fatty acids (Model D), explaining 7.4% of the variability in hair Δ¹⁹⁹Hg (compared to 1.6% of the variability, explained by daily MeHg intake from rice). Serum omega-3 fatty acids are a biomarker for fish consumption.²⁵ In this cohort, serum omega-3 fatty acids were weakly, positively correlated with fish MeHg intake (Spearman's rho: 0.15), and the number of fish meals ingested weekly (Kruskal–Wallis, p = 0.03) (Tables S22–S23†). As noted above, biomarkers have less measurement error compared to estimates derived from self-report FFQs.³⁹ Thus, it was not surprising that serum omega-3 fatty acids were more predictive of hair Δ¹⁹⁹Hg, compared to other measures of dietary MeHg intake for fish and rice, which were derived from the self-report FFQ.

Unlike hair Δ¹⁹⁹Hg, hair δ²⁰²Hg was not associated with rice or fish ingestion in the adjusted models (Models A–D), which was consistent with previous studies.^{10–13,15,16} Instead, hair δ²⁰²Hg was strongly, negatively associated with hair THg, explaining 27–29% of the variability in hair δ²⁰²Hg values (Fig. 2a). The associations between hair δ²⁰²Hg and hair THg were not likely attributed to the dietary source of MeHg because all models were adjusted for rice/fish ingestion. Moreover, in a subset of 15 hair samples corresponding to the third trimester, the same negative trends were observed between hair δ²⁰²Hg and MeHg (Fig. S2a†).

In prior studies, hair δ²⁰²Hg fractionation was thought to mainly reflect MeHg metabolism, in particular, demethylation by gut microbiota.^13,19 However, fractionation of stable isotopes also results from metal binding.⁴⁰ Bonds involving high oxidation states [e.g., iron (Fe³⁺) and copper (Cu²⁺)] prefer heavy isotopes, whereas bonds with sulfur (S), including cysteine and methionine, favor light isotopes.⁴¹ Note that the terms “light” and “heavy” are analogous to “depleted” and “enriched,” respectively. For example, in mice, zinc (Zn) bonding with phosphates in bones resulted in more enriched δ⁶⁶Zn, while δ⁶⁶Zn in the liver was isotopically lighter, reflecting fractionation with cysteine-rich bonds.⁴² In human subjects, blood δ⁶⁵Cu and δ³⁴S were isotopically lighter among hepatocellular carcinoma patients, compared to healthy controls, potentially reflecting reallocation of Cu from the liver and binding to cysteine-rich proteins.⁴⁰

Like other metals, Hg has a high affinity for thiols.⁴³ Lower δ²⁰²Hg has been observed in the presence of thiols,^44,45 which was consistent with the notion that cysteine (with its thiol side-chain) favors lighter isotopes.⁴¹ Using thiol resins, stable Hg isotopes were analyzed in Hg-thiol complexes and in dissolved Hg species, in nitrate and chloride solutions.⁴⁵ In both solutions, thiol-bound Hg had lower δ²⁰²Hg, compared to dissolved Hg species.⁴⁵ Similarly, in soil the cysteine-bound fraction of Hg had lower δ²⁰²Hg, compared to the bulk soil.⁴⁴ Moreover, cysteine in soil was also associated with higher uptake and translocation of MeHg in rice roots and stems, compared to other thiol-containing compounds, including glutathione and penicillamine.⁴⁶

Due to the high affinity of MeHg for thiols, transport processes in biological systems typically act on MeHg conjugates with either cysteine or glutathione.¹ For example, in the human body, MeHg enters the cells as a complex with the amino acid L-cysteine and exits the cell as a complex with reduced glutathione.¹ Similarly, in human hair, MeHg enters the keratinocytes as a MeHg-cysteine complex.^47,48 In the present study, because hair δ²⁰²Hg decreased as hair THg increased, our results suggested that hair THg (most of which was MeHg)²⁶ was likely bound to cysteine, which favors light isotopes,^41,42 and that light isotopes were preferentially transported into the hair follicle. However, further research could help test this hypothesis.

Hair Δ¹⁹⁹Hg was also negatively associated with hair THg, explaining 1.8–3.6% of the variability in the adjusted models (Tables 1–4 and Fig. 2b). As noted above, a previous study reported lower δ²⁰²Hg for Hg-thiol complexes compared to dissolved Hg species; however, the same was not observed for MIF (Δ¹⁹⁹Hg and Δ²⁰¹Hg).⁴⁵ In fact, slightly higher MIF was observed in the presence of thiols, compared to dissolved Hg species.⁴⁵ More research is needed to understand the potential mechanisms contributing to the observed negative association between hair Δ¹⁹⁹Hg and hair THg.

For the subset of 15 mothers with paired hair measurements reflecting both second and third trimester exposures, hair δ²⁰²Hg was significantly lower during the third trimester compared to the second trimester, while hair Δ¹⁹⁹Hg did not differ between trimester exposure periods (Fig. 3 and S1†). Our results suggested no changes in the dietary sources of MeHg (rice versus fish) between the second and third trimesters. However, as noted above, changes in isotopic abundances of hair δ²⁰²Hg may reflect metabolism, potentially via the gut microbiome (i.e., demethylation).^13,19 This explanation was consistent with prior studies reporting overall changes in the maternal gut microbiome between early/last gestation.⁴⁹ For example, among 24 pregnant mothers in South Carolina, changes in gut microbiota diversity and associations with MeHg concentrations in biomarkers (after controlling for hemodilution) were observed between early/late gestation.⁵⁰ Findings from the present study were limited to just 15 mothers, and longitudinal studies within a larger cohort could improve our understanding of associations between MeHg concentrations in biomarkers and gestation.

Although our study has several strengths, there are some limitations to note. Among non-farmers (n = 62), who ingested more fish compared to farmers (Table S3†), we did not observe the same associations between hair Δ¹⁹⁹Hg and rice MeHg intake that were observed among the entire cohort (Tables 3 and S8†), potentially because of lower rice consumption or because this sensitivity analysis was underpowered. However, we observed a strong, positive association between hair Δ¹⁹⁹Hg and omega-3 fatty acids among the entire cohort (Tables 4 and S9†), suggesting this association was valid regardless of the primary dietary MeHg source (fish or rice). Additionally, we did not analyze whether hair Hg was bound to cysteine, although the MeHg-cysteine complex is the dominant form of MeHg in human hair.⁴⁷ It is important to measure MeHg complexes in hair to confirm our findings regarding uptake of lighter Hg isotopes in human hair. Our study focused on peripartum mothers; however, more studies are needed in the general population to assess these findings. There were likely other factors, including other components of the diet, that contributed to MeHg exposure and metabolism, which were not measured in this study.

Conclusions

In a population where rice was the primary (although not exclusive) dietary source of MeHg, our results indicated that hair MIF (Δ¹⁹⁹Hg) can be used to distinguish dietary sources of MeHg (rice versus fish). This association was validated using maternal serum omega-3 fatty acids (a biomarker for fish consumption)²⁵ and MeHg intake from rice. The data from this study can be further used to develop and inform non-invasive metrics for assessing dietary MeHg exposure in general and sensitive populations. Our results suggested that MeHg metabolism during pregnancy differed between second and third trimesters, although the dietary sources of MeHg did not differ. Lastly, our results also suggested that the Hg isotopic composition in hair, especially MDF, may reflect the complex factors related to MeHg binding and accumulation, or degradation prior to deposition in the hair. Thus, it may be possible to apply Hg stable isotopes to study the trafficking of MeHg between tissues and impacts to human health, as was investigated using other metal isotopes.^40–42

Data availability

All isotope data and hair Hg data used in this study are available in the ESI† associated with this work (Dataset S1), and other data are available upon reasonable request.

Author contributions

Sarah E. Rothenberg: conceptualization; funding acquisition; investigation; supervision; project administration; data curation; methodology; formal analysis; visualization; writing— original draft; writing—review & editing; Susan A. Korrick: conceptualization; funding acquisition; methodology; formal analysis; writing—review & editing; Donald Harrington: formal analysis; writing—review & editing; Sally W. Thurston: funding acquisition; methodology; formal analysis; writing—review & editing; Sarah E. Janssen: investigation; resources; writing—review and editing; Michael T. Tate: investigation; resources; YanFen Nong: project administration; supervision; investigation; resources; Hua Nong: project administration; Jihong Liu: conceptualization; supervision; writing—review and editing; Chuan Hong: Investigation; Fengxiu Ouyang: writing: review and editing.

Conflicts of interest

The authors declare no competing interests.

Acknowledgements

This study was funded in part by a grant from the U.S. National Institute of Environmental Health Sciences at the U.S. National Institute of Health (NIH/NIEHS) to Sarah E. Rothenberg (grant #R21 ES032600). This work was also supported by the University of Rochester Environmental Health Sciences Center, an NIH/NIEHS-funded program (P30 ES001247). This research was supported by the U.S. Geological Survey Environmental Health Program. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The survey described in this information product was organized and implemented by the study team during the enrollment period and was not conducted on behalf of the U.S. Geological Survey.

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Footnote

† Electronic supplementary information (ESI) available: Detailed methods, Fig. S1 (second/third trimester comparison), Fig. S2 (Hg isotopes, THg, and MeHg in the third trimester), Table S1 (all studies reporting hair Hg isotopes), Table S2 (quality assurance/quality control), Table S3 (farmer/non-farmer comparison of biomarkers), Table S4 (with/without Hg isotopes comparison of characteristics), Table S5 (with/without Hg isotopes comparison of biomarkers), Tables S6–S21 (four sets of sensitivity analyses), Table S22 (Spearman's correlation for continuous maternal characteristics), Table S23 (Associations for categorical maternal characteristics), legend for Dataset S1 and references. All isotope data and hair Hg data used in this study are available in the Electronic Supporting Information associated with this work (Dataset S1), and other data are available upon reasonable request. See DOI: https://doi.org/10.1039/d4em00231h

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