A systematic review: On the mercaptoacid metabolites of acrylamide, N-Acetyl-S-(2- carbamoylethyl)-L-cysteine.

doi:10.21203/rs.3.rs-2562586/v1

Download PDF

Research Article

A systematic review: On the mercaptoacid metabolites of acrylamide, N-Acetyl-S-(2- carbamoylethyl)-L-cysteine.

https://doi.org/10.21203/rs.3.rs-2562586/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 17 Jul, 2023

Read the published version in Environmental Science and Pollution Research →

You are reading this latest preprint version

Acrylamide is widely found in various types of fried foods and cigarettes, and is not only neurotoxic and carcinogenic, but also has many potential toxic effects. The current assessment of acrylamide intake through dietary questionnaires is confounded by a variety of factors, which poses limitations to safety assessment. In this review, we focus on the levels of AAMA, the urinary metabolite of acrylamide in humans, and its association with other diseases, and discuss the current research gaps in AAMA and the future needs. We reviewed a total of 25 studies from eight countries. In the general population, urinary AAMA levels were higher in smokers than in nonsmokers, and higher in children than in adults; the highest levels of AAMA were found in the population from Spain compared with the general population from other countries. In addition, AAMA is associated with several diseases, especially cardiovascular system diseases. Therefore, AAMA, as a biomarker of internal human exposure, can reflect acrylamide intake in the short term, which is of great significance for tracing acrylamide-containing foods and setting the allowable intake of acrylamide in foods.

Acrylamide

Biomarker

AAMA

Exposure

Urine

Metabolite

Acrylamide (AA) is commonly used in industry for gel experiments, water purification, and plastic production(Friedman 2003; E. A. Smith and Oehme 1991), workers can be exposed to acrylamide through the skin and respiratory tract. In addition, smoking and diet in daily life are potential sources of acrylamide exposure for the general population. Then, AA is widely found in foods such as French fries and bread, and is formed by the Maillard reaction between free aspartic acid and reducing sugars at high temperatures(Mottram, Wedzicha, and Dodson 2002; Stadler and Scholz 2004). Due to the widespread presence of acrylamide in foods, several studies have estimated dietary acrylamide exposure(Andačić et al. 2020; Eicher et al. 2020; Kawahara et al. 2019). Studies have found that consumer estimates of average intake of AA may vary by country and dietary habits but the average intake can be considered to be about 0.4 µg/kg per day, with an average intake of about 1.0 µg/kg for advanced consumers(Chuang, Chiu, and Chen 2006).

Acrylamide is readily soluble in water and can be rapidly absorbed in the body as well as rapidly distributed in various tissues(Chaudhry, Cotterill, and Watkins 2006). Acrylamide is metabolized in vivo by two pathways, the first being biotransformation via cytochrome P450 (CYP2E1) to produce GA (glycidyl amide) (Calleman, Bergmark, and Costa 1990; Duale et al. 2009), the second pathway is coupled to glutathione in the presence of glutathione S-transferase (GST): acrylamide to N-Acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA), glycidyl amide to N-Acetyl-S-(2-carbamoyl-2-hydroxyethyl)-L-cysteine (GAMA) (S. C. Sumner, MacNeela, and Fennell 1992). Metabolites of acrylamide and glycidyl amide are excreted in the urine as thioglycolic acid derivatives(Eva K. Kopp et al. 2008).

The risk of human exposure to acrylamide is usually estimated based on its occurrence in food, and a health reference value is determined by comparing this risk to the baseline lower confidence limit for dose in animals (BMDL 10) (Chain (CONTAM) 2015), however, this method is influenced by various factors such as dietary frequency and bias in the estimation of acrylamide levels in food. Therefore, human biomonitoring (HBM) is currently used to obtain exposure to acrylamide in urine or blood to better estimate total exposure (Goerke et al. 2019; Pedersen et al. 2022). In general, urine is the specimen of choice for acrylamide biomonitoring (F Fernández et al. 2022), because of its stability, high specificity and sensitivity, and its easy availability in large quantities (Louro et al. 2019).

Urinary metabolite levels of acrylamide have been reported in several studies(Thomas Bjellaas et al. 2007; Melanie Isabell Boettcher et al. 2005; Ruenz et al. 2016; S.-Y. Wang et al. 2020). Due to the high enzymatic activity of CYP2E1, AA is more readily metabolized oxidatively than GA. In a study of urinary acrylamide metabolism in mice, a GAMA/AAMA ratio of 0.23 was calculated(Twaddle et al. 2004). Sumner et al. also found that AAMA accounted for 41% of total urinary metabolites and GAMA for only 21% after oral administration of 50 mg/kg AA body weight to mice, with a GAMA/AAMA ratio close to 0.51(S. C. J. Sumner et al. 2003), and the same was found in the population metabolic pattern(Mojska et al. 2020). AAMA seems to be more advantageous than GAMA in excretion, but GAMA is converted from GA, which may play a role in cancer, neurotoxicity, etc. Therefore, GAMA/AAMA ratio has been explored again as a specific indicator of AA metabolic activation. However, a recent study has shown that the GAMA/AAMA ratio changes substantially even in a single participant after oral acrylamide administration due to differences in the elimination kinetics of the two metabolites(T. Bjellaas et al. 2005; Melanie I. Boettcher et al. 2006). Therefore, this ratio is unreliable for assessing potential polymorphisms between individuals, so using a single AAMA as a short-term exposure biomarker remains advantageous.

The health effects of acrylamide have received increasing attention in recent years, and its neurotoxicity has been demonstrated in occupational populations(He et al. 1989). The general symptoms of neurotoxicity in humans are skeletal muscle weakness, ataxia, weight loss, and axonal degeneration of the central and peripheral nervous system(Hagmar et al. 2001). Studies have found that the specific neurotoxicity index (Nin) of acrylamide-induced peripheral neuropathy correlates with workers' 24-hour urine Mercapturic acid levels in the urine of workers were significantly correlated(Calleman et al. 1994). In addition, the carcinogenicity of acrylamide has been well documented in experimental animals(Klaunig 2008). Therefore, acrylamide has been classified by the World Health Organization's International Agency for Research on Cancer (IARC) as a "probable human cancer risk"(IARC 1994, 60). Studies on dietary acrylamide and hemoglobin adducts and various cancers have been reported repeatedly(Kito et al. 2020; Obón-Santacana et al. 2016; Zha et al. 2020), but studies on cancer and urinary biomarkers of acrylamide are scarce, and only a dose-response relationship between urinary AAMA and uroepithelial carcinoma (UC) has been found(Chung et al. 2020). Therefore, studying the role of urinary biomarkers of acrylamide will help researchers to discuss its relationship with various diseases in the future.

With this review, we aim to summarize the published levels of the urinary metabolite of acrylamide, AAMA, as a reference for the exposure dose in the studied population. In addition, we discuss the association of AAMA with other factors and diseases, aiming to illustrate the role of the urinary metabolite of acrylamide, AAMA, and to explore research gaps and future needs.

We searched the Embase online database to identify peer-reviewed studies that reported mean levels of the acrylamide urinary metabolite AAMA or its association with factors such as other diseases. The search strategy was: acrylamide and metabolites. The exact search term is: ("acrylamide"[Title/Abstract] OR "acrylamides"[Title/Abstract]) AND "metabolites"[Title/Abstract]. All articles retrieved were imported into Endnote 21, and duplicates were removed. Titles and abstracts were screened by two independent reviewers, and potentially relevant articles were identified from the reference lists of the included articles. The criteria for inclusion of articles in the review were: human studies, with AAMA-related measures (mean/median, R-value). All included studies were published in English through August 2022. Data were organized and plotted using Review Manager 5.4, IBM SPSS Statistics 21, and GraphPad Prism8.

We retrieved 186 articles on human acrylamide urine metabolites and 1 additional study from the reference list. The selection process is shown in Figure.1. After discussion, 25 articles were selected for review, 16 studies reported AAMA levels (mean/median), and 10 studies reported correlations of AAMA with other indicators and diseases, with 1 study including both.

3.1. Quantification of AAMA levels of acrylamide in the general population

A total of 16 studies reported levels of the urinary biomarker AAMA for acrylamide in the general population, with a total of 5555 individuals. We describe these studies by country and year of publication (Table 1).

Table 1

Characteristics of individual studies of urinary metabolites of acrylamide in the general population
Study	Location	Year		AAMA levels(µg/L)
(Mojska et al. 2020)	Poland	2020	A total of 67 non-smokers and 10 women who were passive smokers during pregnancy were enrolled to determine AAMA and GAMA levels in urine samples using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS).	Median (min-max) Non-smokers 19.5 (2.3–114) Smokers 21.6 (9.0-73.9)
(Heudorf, Hartmann, and Angerer 2009)	Germany	2009	One hundred and ten children aged 5–6 years were randomly selected, their eating habits were investigated by questionnaire.	Median(${P}_{95}$) AAMA : 36.0༈152.7༉
(T. Bjellaas et al. 2005)	Norway	2005	A pilot study was conducted with 11 smokers and 65 non-smokers in which all urine was collected and quantified over a 48-hour period starting with a 24-hour fast.	Median (min-max) Overall: 35(10–500) Non-smokers༚ 29(10–178) Smokers༚337༈64–500༉
(Schwedler et al. 2021)	Germany	2021	Early morning urine samples from 2259 children and adolescents (2211 non-smokers and 48 smokers) aged 3–17 years were sampled and quantitatively analyzed.	Median (min-max) Overall: 72.6 Non-smokers: 71.08 (68.89–73.34) Smokers: 191.3 (155.5-235.2)
(Moorman et al. 2012)	American	2011	Urinary metabolites were measured in different types of workers in three factories (administrative workers were selected as the general population) n = 13.	Median AAMA:8(5.6–9.4)
(Mojska et al. 2016)	Poland	2016	Metabolites of acrylamide and glycidyl amide concentrations (AAMA and GAMA, respectively) in the urine of 93 women during the first days after delivery were determined using LC-MS / MS.	Median(${P}_{5}-{P}_{95}$) AAMA:20.9(2.3–399.0)
(Lee et al. 2014)	Korea	2014	Urinary AAMA was assessed in the Korean adult population aged 18–69 years. n = 1870 The mean age of the subjects was 45.5 years and 43.0% of the sample was male.	Mean(min-max) AAMA:30.0(28.2–31.8)
(Eva K. Kopp et al. 2008)	Germany	2008	Liquid chromatography tandem mass spectrometry was used to quantify the levels of AAMA and GAMA and AAMA-sul in human urine, and samples were obtained from 54 urines of 6 individuals.	Median(min-max) AAMA: 24.0(7.8–79.8)

Table 1

(continued)
(Hartmann et al. 2008)	Germany	2008	To determine the relationship between the oxidative and reductive metabolic pathways of acrylamide (AA) in the general population of non-smokers. Quantification of hemoglobin adducts and urinary metabolites. (n = 91)	Median(min-max) AAMA: 29(< 1.5–229)
(Frigerio et al. 2020)	Italy	2020	Sixty-seven healthy adults with different smoking habits were investigated: 38 non-smokers (NS), 7 electronic cigarette users (ECU) and 22 traditional smokers (TTS), and their urine was quantitatively analyzed.	Median(${P}_{5}$-${P}_{95}$) NS: 47.9༈24.2–95.4༉ ECU༚55.8༈34.4–65.5༉ TTS༚ 114.6༈55.1-223.9༉
(F Fernández et al. 2022)	Spain	2022	Urine samples were analyzed from 120 breastfeeding mothers aged 20–45 years living in Spain.	Geometric mean(range) AAMA:70 (NA)
(Fernández et al. 2022)	Spain	2022	Exposure to AA was assessed in Spanish children (n = 612).	Geometric mean(range) AAMA:79(NA)
(Boyle et al. 2016)	American	2016	Urine samples from 488 pregnant women in late pregnancy were collected for quantification.	Median(range) AAMA:33.3(NA)
(Melanie Isabell Boettcher and Angerer 2005)	Germany	2005	LC-MS / MS method for the quantitative determination of levels of AAMA, the mercapturic acid metabolite of acrylamide (AA), and GAMA, the mercapturic acid metabolite of its oxidized metabolite glycidyl amide (GA), in the general population. Thirteen smokers and 16 non-smokers were included.	Median (min-max) Overall : 60(< 1.5–338 ) Smokers༚127(17–338) Non-smokers༚29(< 1.5–83)
(Thomas Bjellaas et al. 2007)	Norway	2007	In a clinical study including 53 subjects, excretion of urinary metabolites of acrylamide was determined using solid-phase extraction and liquid chromatography.	Median (min-max) Overall : 18 (7-106) Smokers : 74 (38–106) Non-smokers : 16 (7–47)
(Ji et al. 2013)	Korea	2013	In Korean children (n = 31, 10–13 years old), levels of the major AA metabolite: N-acetyl-S-(2-aminocarbonylethyl)-cysteine (AAMA) were collected in urine samples twice at 3-d intervals.	Median (min-max) 68.1(15.4-196.3)
NA: Not Available.

Five of these studies were from Germany, two from Norway, two from Poland, two from Korea, one from Italy, two from Spain, and two from the United States. Fourteen of these studies documented overall AAMA levels, while the other 2 studies quantified AAMA levels by grouping only according to whether or not they smoked. Second, 8 of the 16 studies documented mean or median urinary AAMA in both the smoking and nonsmoking populations.

3.2. Possible influencing factors causing AAMA differences

For the studies included in Table 1, we stratified the AAMA levels of the study subjects and explored the reasons for the differences in AAMA in terms of whether they smoked, the country in which the study subjects lived, and their age. Studies of the general population relied on small groups of adults (N < 1000), and fewer studies were conducted on children and older adults. Of the 16 studies, only 1 study had a sample size of more than 1000 individuals.

3.2.1. Smoking

The metabolism of acrylamide was highly variable between individuals (Figure.2). Urinary AAMA levels ranged from 8-71.08 µg/L in nonsmokers and 17-191.3 µg/L in smokers, and the mean/median urinary AAMA levels were approximately 2-fold higher in smokers compared to non-smokers.

3.2.2. Living Country

Acrylamide urinary metabolite AAMA levels varied substantially even among people from the same country (Table 1). After combining smokers and nonsmokers, the original studies were categorized by country to compare their urinary AAMA mean/median levels (Figure.3).

The mean urinary AAMA level was higher in individuals from Spain compared to other countries, with a mean value of 74.5 µg/L. Individuals from the United States, Korea, Italy, Poland, Norway, and Germany all had AAMA levels in the range of 20 ~ 60 µg/L.

3.2.3. Age

Three studies were conducted in children and adolescents from Germany (n = 2369) and Korea (n = 31), comparing AAMA levels in children with adult populations, with children having slightly higher urinary AAMA levels. (The results are shown in Figure.4).

3.3. Correlation study

A total of 10 studies reported the association of AAMA with other factors and diseases, nine of these studies were from China and one from Poland, two of which(B. Wang et al. 2021; B. Wang, Qiu, et al. 2020) were from the same population (Table 2).

Table 2

Association of urinary metabolite AAMA with other indicators and diseases in the original study.
Study	Location	Year	Study description	Results
(B. Wang, Qiu, et al. 2020)	China	2020	The association of urinary acrylamide metabolite AAMA with 8-OHdG (urinary 8-hydroxydeoxyguanosine), 8-iso-PGF2α (8-iso-prostaglandin-F2α) and FPG (fasting plasma glucose) was assessed by linear mixed models in 3,270 general adults from the Wuhan-Zhuhai cohort.	FPG increased by 0.17 mmol/L for each 1-unit increase in log-transformed levels of AAMA (P < 0.05). 8-OHdG increased by 0.19% and 8-iso-PGF2α increased by 0.40% for each 1% increase in AAMA(P < 0.05).
(B. Wang et al. 2021)^a	China	2021	The relationship between urinary acrylamide metabolites, lung function and plasma CRP was assessed in 3271 general population using a linear mixed model, and the mediating role of CRP was assessed using the PRODCLIN procedure.	For each 1-unit increase (P < 0.05) in log-transformed levels of AAMA, FVC decreased by 59.9 mL and FEV decreased by 53.9mL. AAMA (β = 0.10) was significantly (P < 0.05) associated with a significant (P < 0.05) increase in CRP, which in turn mediated a 6.34–11.1% decrease in urinary acrylamide metabolite-related lung function.
(B. Wang et al. 2022)	China	2022	The cross-sectional and longitudinal associations of urinary acrylamide metabolites with 10-year risk of cardiovascular disease (CVD) were assessed.	The cross-sectional and longitudinal association of AAMA with increased 10-year CVD risk was: OR (95% CI): 1.32 (1.04, 1.70) RR (95% CI): 1.99 (1.10, 3.60).
(B. Wang, Cheng, et al. 2020)	China	2022	The exposure-response relationship and potential mechanisms between internal acrylamide exposure and altered heart rate variability (HRV), a marker of cardiac autonomic dysfunction, were explored.	After adjusting for potential confounders, all urinary acrylamide metabolites and TGF-β1 were significantly negatively correlated with the dose-response relationships of the six HRV indices(P < 0.05).
(Mojska et al. 2016)	Poland	2016	The correlation between dietary intake of acrylamide and urinary metabolites was explored.	There was a weak but significant positive correlation between acrylamide intake calculated from urinary AAMA and GAMA levels and acrylamide intake estimated from 24-hour dietary recall (R = 0.26, P < 0.05).
(Liao et al. 2022)	China	2022	The correlation between dietary intake of acrylamide and urinary metabolites was explored.	Increased intake of oily snacks (β = 0.335, P = 0.012) and weekly intake of sweetened beverages would increase urinary AAMA concentrations in the 6–11 years group (β = 0.322, P = 0.018) and in the 12–18 years group.

Table 2

(continued)
(Y.-F. Huang et al. 2011)	china	2011	The relationship between the acrylamide metabolite AAMA and genetic polymorphisms of the metabolic enzymes cytochrome P450 (CYP2E1), microsomal epoxide hydrolase (mEH) exon 3 and exon 4, and glutathione transferase θ(GSTT1) and µ (GSTM1) was investigated.	The GSTM1 genotype significantly altered urinary AAMA excretion, and exon 4 of mEH was significantly associated with urinary GAMA levels after adjustment for AA exposure.
(C.-C.J. Huang et al. 2015)	china	2015	Potential association of urinary N7-(2-carbamoyl-2-hydroxyethyl)guanine with dietary acrylamide intake in smokers and nonsmokers.	Correlation between AAMA and N7-GAG: non-smokers: R = 0.463 (P = 0.007) smokers: R = 0.461 (P = 0.010) all study participants: R = 0.479 (P < 0.001).
(Hsu et al. 2020)	china	2020	Determined if AAMA and GAMA were associated with CV risk markers in children with CKD (chronic kidney disease).	Cardiovascular risk markers: urinary acrylamide levels were associated with 24 h SBP (R = -0.368, P = 0.001), daytime SBP (R = -0.373, P = 0.001), nighttime SBP (R = -0.356, P = 0.002), 24 h DBP (R = -0.32, P = 0.005), daytime DBP (R = -0.31, P = 0.007), nighttime DBP (R = -0.234, P = 0.045), and LV mass (R = -0.566. P < 0.001).
(Chung et al. 2020)	china	2020	The relationship between urinary levels of cotinine and VOC (organic compound) metabolites (acrylamide, 1,3-butadiene and benzene) and the risk of UC was explored.	Correlation between AAMA and risk of uroepithelial cancer (R = 0.17, P = 0.0004) (P = 0.0007).
CI: Confidence Interval;
^a Same individuals as in (B. Wang, Qiu, et al. 2020).

A total of 16 peer-reviewed studies reported urinary metabolite AAMA levels of acrylamide from 7 countries corresponding to 5555 individuals. A total of 10 studies reported the association of AAMA with other indicators and diseases.

4.1. Urine AAMA as a biomarker of exposure in the short term

4.1.1. Advantages of AAMA over several other mercapturic acid metabolites

There are four recognized metabolites of acrylamide mercapturic acid, which are: N-Acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA),N-Acetyl-S-(2-carbamoyl-2-hydroxyethyl)-L-cysteine(GAMA),N-acetyl-3-[(3-amino-3-oxopropyl)sulfinyl]-L-alanine(AAMA-sul),N-acetyl-S-(1-carbamoyl-2-hydroxy-ethyl)-L-cysteine(iso-GAMA)(Melanie I. Boettcher et al. 2006), these metabolites are present in different proportions in the body.

Fennel et al. investigated the metabolic characteristics of acrylamide in volunteers and found that after administration of 0.5 mg/kg body weight acrylamide, the total amount of metabolites excreted by volunteers within 24 hours were 145, 38.2, 3.1 and 0.7 µmol (AAMA, AAMA-Sul, GAMA and iso-GAMA)(Fennell et al. 2006). GAMA and iso-GAMA are oxidized mercapturic acids, Eva C Hartmann et al. compared the metabolic excretion process of AAMA, GAMA, and iso-GAMA and found that AAMA was excreted much faster with an estimated elimination half-life of 11 h, whereas GAMA and iso-GAMA were excreted slower and took longer, and the elimination half-life was estimated to be 19 h, which this may be influenced by the ability and activity of CYP2E1 oxidase and glutathione transferase(Hartmann et al. 2009). In addition, AAMA-Sul is formed by the oxidation of AAMA in humans, which has not been demonstrated in rodents, and there are fewer studies on the mechanism of AAMA-Sul formation (Fennell et al. 2006; Eva Katharina Kopp and Dekant 2009). Therefore, compared with several other acrylamide sulfhydryl ate metabolites, AAMA is more responsive to short-term exposure.

4.1.2 Dietary intake of acrylamide in the short term can be deduced from urine AAMA levels

The estimation between dietary acrylamide intake and its urinary metabolite levels has been widely used in epidemiological studies(Melanie I. Boettcher et al. 2006; Fennell et al. 2006; Fuhr et al. 2006), and this quantification contributes to the risk assessment of acrylamide. For example, a comparison of this amount with dietary acrylamide intake can encourage the population to improve dietary habits and prevent the adverse toxic effects of acrylamide. Based on the daily urinary AAMA excretion, the daily intake of acrylamide can be estimated as follows (Eq. 1).

$$A=\frac{{M}_{AA}*{AAMA}_{urine}}{{M}_{AAMA}*0.5}*{C}_{n} \left(1\right)$$

Among them,

${AAMA}_{urine}\text{i}\text{s} \text{t}\text{h}\text{e} \text{m}\text{a}\text{s}\text{s} \text{o}\text{f} \text{A}\text{A}\text{M}\text{A} \text{e}\text{x}\text{c}\text{r}\text{e}\text{t}\text{e}\text{d} \text{i}\text{n} \text{t}\text{h}\text{e} \text{u}\text{r}\text{i}\text{n}\text{e} \text{e}\text{v}\text{e}\text{r}\text{y} \text{d}\text{a}\text{y}$ (µg/g);

${\text{C}}_{\text{n}}$ is the daily creatinine excretion (g);

${M}_{AAMA}$ and ${M}_{AA}$ are the molecular weights of AAMA and AA, respectively (234.1 and 71.1).

However, the estimation of dietary acrylamide intake by formula 1 alone is not reliable, because the collection of 24h urine is difficult to ensure in practice, and urine concentration is affected by fluid intake, season, temperature and other factors (Mage, Allen, and Kodali 2008). In 1963, Vought and London first proposed the use of urinary creatinine adjustment to estimate the 24h iodine excretion from a single random urine sample, because the excretion of creatinine is relatively stable throughout the day(Knudsen et al. 2000; Ohira et al. 2008; Tanaka et al. 2002; Vought et al. 1963; Vought and London 1964). However, Vought and London only considered gender factors. With the maturity of technology and knowledge, scientists have developed a more optimized method to estimate 24-hour secretion excretion with creatinine reference value, and only gender, age, weight and height are needed to estimate urinary creatinine level(Johner et al. 2015).

Reference values for urinary creatinine in adults have been reported several times, most specifically by Mage et al. who derived predictive equations specific to adult males and females (equations (2) and (3)) based on established equations converted by body surface area to estimate daily creatinine excretion containing height, weight, and age functions(Mage et al. 2004). However, urinary creatinine can vary depending on anthropometric factors and ethnicity, and therefore the reference values for urinary creatinine in children differ from those in adults. There are currently only two studies on creatinine reference values in children: In the first study, Remer et al. reported creatinine measurements in 24-hour urine samples from 225 boys and 229 girls, in which, the mean creatinine excretion rate was 17 mg/kg/day in children under 14 years of age and 22 mg/kg/day in children 14–18 years of age (Remer, Neubert, and Maser-Gluth 2002). In the second study, Wei Wang et al. studied the mean 24h urinary creatinine excretion in Chinese children aged 8–13 years in 2018, and developed reference values for 24h urinary creatinine excretion in boys and girls with different heights and weights(W. Wang et al. 2018).

$${Male C}_{n}=1.93\left(140-A\right)*{BW}^{1.5}*{h}^{0.5} （2）$$

$${ Female C}_{n}=1.64\left(140-A\right)*{BW}^{1.5}*{h}^{0.5} （3）$$

The 24-hour excretion of certain analytes in urine can be calculated by multiplying the analyte with the age - and sex-adjusted urinary creatinine ratio (W. Wang et al. 2018), therefore, dietary acrylamide intake can be estimated by combining the above two formulas, but the precondition is that the exposure of acrylamide remains stable for a long time.

4.1.3 AAMA for urinary metabolites of acrylamide: detectability, accessibility, accuracy

For the determination of acrylamide urine metabolites, various versions of LC-MS/MS methods have been used in national studies. T Bjellaas et al. developed a solid-phase extraction and liquid chromatography method with positive electrospray (LC-ESI-MS/MS), which was the first to use NMR spectroscopy for the identification of acrylamide mercapturic acid metabolites, and it had an AAMA detection limit ( c-LOD) was 1.0 µg/L(T. Bjellaas et al. 2005). Subsequently, Eva K Kopp et al. developed a hydrophilic interaction liquid chromatography tandem mass spectrometry (HILIC-MS/MS) using Zic-HILIC stationary phase (ZIC-HILIC), which can reduce the interference of various factors on urinary matrix to a greater extent, but also improve the sensitivity, the detection limit of AAMA was only 0.5µg/L(Eva K. Kopp et al. 2008). In 2015, Yu Zhang et al. developed an isotope dilution ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) (Zhang et al. 2015), and the c-LOD of AAMA can reach 0.1–0.3µg/L. There have been a number of reviews on the isolation and detection of acrylamide urine biomarkers, and researchers have summarized the advantages and disadvantages of various detection methods (Mathias and B’Hymer 2014; Mathias and B’hymer 2016). In general, MS/MS provides high sensitivity for the analysis of sulfhydryl compounds, and advances in various techniques have made the determination of AAMA levels more proficient.

Collecting urine is easier and non-invasive than collecting blood. Acrylamide Hb adducts are a biomarkers of long-term exposure(Pedersen et al. 2022), the intake of acrylamide cannot be accurately quantified through dietary recall, and the red blood cells required for its detection can only be obtained through blood collection, which undoubtedly increases the burden and work of participants. Acrylamide can also combine with DNA and other proteins, but its reactivity is very low and only glycidyl amide can form DNA adduction, which can be easily repaired after formation(Segerbäck et al. 1995). In addition, the leukocyte storage conditions required for the detection of acrylamide DNA adduction are higher. Therefore, compared with Hb adduct and DNA adduct, acrylamide urine metabolite AAMA can reach the detection peak within a few hours and decompose rapidly(Melanie I. Boettcher et al. 2006). In humans, the half-life of AAMA is estimated to be 17h(Fuhr et al. 2006), while the half-life of GAMA is longer than that of AAMA by several days(Miller, Carter, and Sipes 1982). Similar results were obtained by Melanie I Boettcher et al(Melanie I. Boettcher, Bolt, and Angerer 2006), who fasted for 48 hours in 3 healthy volunteers to study AAMA excretion and found that the maximum urine values of 114, 178, and 317 µg/L, respectively, were compared to those measured at the beginning of the fast (mean: 203 ± 104µg/L), the urinary mercapto concentration was reduced by about 95% after fasting for 48h. Therefore, compared with hemoglobin adduction, DNA adduction and GAMA, AAMA has a shorter half-life and can reflect the intake of acrylamide in the short term, which provides a basis for tracing the foods that may contain acrylamide and helps to quantify acrylamide content in various foods. Moreover, short-term study avoids recall bias.

As acrylamide hemoglobin adducts reflect long-term acrylamide exposure levels, they are more responsive to changes in the internal amount of acrylamide caused by a combination of dietary and smoking factors, and the excretion measured in this case is difficult to match with the actual acrylamide intake, resulting in a low correlation between dietary acrylamide and biomarker excretion (Wirfält et al. 2008). This makes the causes of elevated and decreased urinary excretion unexplained. However, the urinary metabolite AAMA addresses this issue well, as high acrylamide dietary intake must cause elevated urinary AAMA levels(Eva Katharina Kopp and Dekant 2009; Zhang et al. 2015).

4.2 Effects of various factors on urinary AAMA levels

Cotinine is a biomarker of tobacco smoke exposure and its association with acrylamide urinary metabolites has been reported in several studies (Kenwood et al. 2022, 2011–16; D. M. Smith et al. 2021, 2013–14; Sy et al. 2019; Urban et al. 2006). According to an estimate of acrylamide exposure in Polish tobacco smoke, the average amount of acrylamide was 679 nanograms per cigarette (range: 455–798 nanograms per cigarette)(Mojska, Gielecińska, and Cendrowski 2016). The amount of AAMA excreted in the urine of smokers was reported to be 2.5 times higher than that of non-smokers (Urban et al. 2006). Furthermore, in a urinalysis study of male military officers, a statistically significant linear relationship was found between urinary NASPC and cotinine levels in smokers (R = 0.402, P = 0.028)(C.-C. J. Huang et al. 2007). However, the study population reported so far is active smokers, and the association between passive smoking and urinary AAMA levels has not been confirmed (Ji et al. 2013). In the present study, smokers had higher mean urinary AAMA levels than nonsmokers (Fig. 3), with urinary AAMA levels ranging from 8 to 71.08µg/L in nonsmokers and from 17 to 191.3µg/L in smokers. This wide range indicates a large variation in dietary acrylamide exposure, some non-smokers may also become passive smokers.

Acrylamide intake can also fluctuate according to geographic region, as confirmed by a study examining average dietary acrylamide intake among adults in different European countries (Freisling et al. 2013), which found a clear gradient in average intake of acrylamide, such as a specific average intake in the Nordic centers being approximately 3 times higher than in southern Europe. The World Health Organization surveyed the dietary acrylamide intake of children and adults from 17 countries in 2006, among which the average AA intake of the Chinese population was 0.3µg/kg body weight, while the average AA intake of the United Arab Emirates was 2.0µg/kg body weight (Joint FAO/WHO Expert Committee on Food Additives 2006). The reasons for the differences in AA intake in different countries may be due to the differences in research methodology, or the differences in dietary habits. For example, the Dutch and Japanese prefer coffee, fried potatoes and other foods(Hogervorst et al. 2007; Nagata et al. 2015), while the Chinese prefer vegetables and grains(Gao et al. 2016).

There were also differences in urinary AAMA levels in different age groups of people. In the present study, the mean urinary AAMA level was 58.9 µg/L in children and 33.24 µg/L in adults, and urinary metabolite levels were slightly higher in children than in adults, and similar findings were obtained in several other studies(Dybing et al. 2005; Hartmann et al. 2008; Sy et al. 2019). Part of the reason for this difference is the high dietary acrylamide intake in children(Duke, Ruestow, and Marsh 2018; Vesper et al. 2010, 2003–4), the other part is due to differences in metabolic kinetics between children and adults(Walker et al. 2007). For example, toxicant detoxification and clearance processes in children are immature, or in some cases express GST early, and the immaturity in glutathione counteracts glycidyl amide, leading to greater doses of acrylamide aggregation(Cresteil 1998; Hj et al. 2002; Renwick, Dorne, and Walton 2000).

CYP2E1, GST, and mEH are important enzymes in acrylamide metabolism and can also impact the formation of acrylamide urinary mercapturic acid. GA has been reported to be detoxified by microsomal oxide hydrolase (mEH) to glycinamide(Kirman et al. 2003). The studies included herein found that mEH and GSTM1 may be associated with the formation of urinary AAMA and GAMA(Y.-F. Huang et al. 2011). Another study on the toxicokinetic of CYP2E1 affecting AA, AAMA and GAMA3 showed that CYP2E1 may account for a quarter of primary AA metabolism in humans and plays an important role in the binding of AA and GA to glutathione (Doroshyenko et al. 2009). However, it has also been shown that moderate induction of CYP2E1 in humans has no significant effect on the excretion of AA or GA-derived mercapturic acid in urine(Doroshyenko et al. 2009). GST has a broad role in catalyzing a variety of reactions between glutathione and electrophilic compounds, and its isozymes GSTM1 and GSTT1 have been identified to exhibit gene deletion polymorphisms(Strange, Jones, and Fryer 2000). It has also been shown that workers with GSTM1 genotype deficiency have lower urinary AAMA levels (P = 0.057)(Duale et al. 2009).

In addition to the above factors, gender, BMI, education level, and consumption pattern will also affect urinary AAMA level (Lee et al. 2014). Dietary acrylamide intake and acrylamide hemoglobin adduct levels were higher in men than in women (Dybing et al. 2005). In addition, in a study included in this paper participants' body weight was found to be positively correlated with the amount of urinary AA metabolites excreted(R = 0.28, P = 0.05)(Thomas Bjellaas et al. 2007). However, experimental animal studies have shown that exposure to acrylamide can reduce body weight (Ogawa et al. 2011; H. Wang et al. 2010), because acrylamide can affect appetite (Garey and Paule 2007). A negative correlation between acrylamide hemoglobin adducts and body weight was also found in the National Health and Nutrition Examination Survey (Chu et al. 2017, 2003–4), however, the reasons for the differences in the association of body weight with HBAA and AAMA remain to be further explored.

4.3 Associations of AAMA with various indicators and diseases have been reported

2 studies examined the association between dietary intake of acrylamide and urinary metabolites. Hanna Mojska et al. measured the urinary metabolite AAMA in 93 women after delivery and found a weak but significant positive correlation between acrylamide intake based on urinary AAMA and GAMA levels and acrylamide intake estimated from 24-hour dietary recall (R = 0.26, P < 0.05)(Mojska et al. 2016). Kai-Wei Liao et al. studied the relationship between dietary patterns and urinary metabolites of acrylamide in the general population and found that urinary AAMA concentrations increased with increased intake of oily foods and sweetened beverages in people aged 6–18 years (Liao et al. 2022). This is because acrylamide is rapidly metabolized and excreted in the body as AAMA (Melanie I. Boettcher et al. 2006), this conclusion was confirmed in the study by Hanna Mojska et al. Because, even weak changes in dietary acrylamide intake caused significant changes in urinary AAMA levels, which were observed in the short term (Mojska et al. 2016).

Acrylamide, an environmental pollutant, may be a risk factor for the development of cardiovascular disease(Bhatnagar 2004). Oxidative stress and inflammatory status have been reported to be indicators used to identify various chronic diseases, and acrylamide appears to contribute to the progression of atherosclerosis through inflammation (Kim et al. 2015; Yousef and El-Demerdash 2006). The three studies included in this paper examined the association between urinary metabolites of acrylamide and indicators related to cardiovascular function (Hsu et al. 2020; B. Wang et al. 2021, 2022), a study by Bin Wang et al. found that acrylamide may increase cardiovascular risk in the general adult population by inducing oxidative stress, inflammation, and plasma transforming growth factor (TGF-β1), which in turn showed a negative dose-response relationship with altered heart rate variability (HRV), suggesting that daily exposure to acrylamide in the general population is associated with cardiac autonomic dysfunction, which may involve mechanisms of the TGF-β pathway. In addition, cardiovascular disease (CVD), which begins in the early to middle years in children with chronic kidney disease (CKD), is also a major cause of death in children with CKD (Hsu et al. 2020). Chien-Ning Hsu et al. investigated the relationship between AAMA, GAMA and CV risk markers in children with CKD and found that urinary AAMA was negatively associated with high systolic blood pressure (SBP), diastolic blood pressure (DBP) load and left ventricular mass. In addition, it has been shown that the AAMA/AA ratio in urine measures the outcome of acrylamide, with a high ratio indicating that acrylamide binds more to glutathione in the body rather than being converted to glycidyl amide. (Rietjens et al. 2018), and that glutathione appears to be beneficial in reducing CV risk in patients with CKD (Vera et al. 2018). Therefore, the role of various mediators between acrylamide and cardiovascular system diseases should be further explored.

Five other studies explored the association of urinary AAMA with other indicators separately. In the in vivo metabolism of acrylamide, various enzymes play a great role, for example, GA can be hydrolyzed to glycinamide by microsomal epoxide hydrolase (mEH)(Kirman et al. 2003). Two genetic polymorphic loci have been identified for mEH: one in which exon 3 is mutated from T to C, allowing the conversion of tyrosine residue 113 to histidine, resulting in reduced activity of mEH; the other in which exon 4 is converted from A to G, allowing the conversion of tyrosine residue 139 to arginine, resulting in increased activity of mEH (Duale et al. 2009), And Duale et al. also found lower levels of acrylamide hemoglobin adducts in individuals with high activity mEH alleles than in individuals with low activity mEH alleles. However, Yu-Fang Huang et al. investigated the relationship between mEH and glutathione transferase (GSTM1) and urinary AAMA and GAMA and did not find any effect of mEH on urinary mercapturic acid metabolite levels, speculating that the sample size may have limited the statistical inference(Y.-F. Huang et al. 2011). Chih-Chun Jean Huang et al. also found that urinary (2-carbamoyl-2-hydroxyethyl) guanine (N7-GAG) levels could be assessed by urinary AAMA, which is the active agent in acrylamide genotoxicity and the main DNA adduct formed by acrylamide (C.-C. J. Huang et al. 2015). Urinary 8-hydroxydeoxyguanosine (8-OHdG) and 8-iso-prostaglandin-F2α (8-iso-PGF2α) are independent key biomarkers of oxidative DNA damage and lipid peroxidation and play an important role in carcinogenesis and glucose allosteric dysregulation. Additional studies also found that the urinary acrylamide metabolite AAMA showed a linear positive dose-response relationship with 8-OHdG, 8-iso-PGF2α(B. Wang, Qiu, et al. 2020).

4.4 Research Gaps and Future Needs

Although, acrylamide mercapturic acid metabolites are excellent indicators of response to in vivo exposure, most of the current studies on the relationship between acrylamide and diseases such as cancer have mostly applied acrylamide hemoglobin adducts, which seems to be a stereotype already, and future researchers should fully explore the role of urinary biomarkers of acrylamide.

The studies included in this paper were mainly for adults and children, with pregnant women accounting for the majority of adults, and the study participants were under 60 years of age and did not include elderly people, therefore, there is no guarantee that the various associations are applicable to any population. In addition, the calculation of urinary AAMA excretion level by creatinine adjustment method is affected by many factors, and a calculation method combining creatinine adjustment and urine volume adjustment should be developed in the future in order to accurately estimate acrylamide exposure dose in vivo and provide a reference for disease prevention.

In this systematic review, a large number of studies have reported the feasibility of the urinary metabolite of acrylamide, AAMA, as a biomarker of internal exposure. First, it is available in large quantities, simple to assay and noninvasive to participants; second, AAMA is the shortest and most stable urinary metabolite with the shortest half-life and can be used to trace foods that may contain acrylamide based on its excretion rate. Meanwhile, the average level of AAMA in various age groups can provide a basis for the Food Safety Administration to adjust the allowable intake of acrylamide. Finally, the association of AAMA with various diseases and factors also provides a valuable reference for future clinical diagnosis and treatment.

AA Acrylamide

CYP2E1 Phase I toxin metabolizing enzymes

GA glycidyl amide

AAMA N-Acetyl-S-(2-carbamoylethyl)-L-cysteine

GAMA N-Acetyl-S-(2-carbamoyl-2-hydroxyethyl)-L-cysteine

BMDL 10 Lower confidence limit for the baseline dose

Nin Specific neurotoxicity index

IARC World Health Organization International Agency for Research on Cancer

UC Uroepithelial cancer

8-OhdG 8-hydroxy-deoxyguanosine

8-iso-PGF2α lipid peroxidation (8-iso-prostaglandin-F2α)

FPG Fasting Plasma Blood Glucose

CRP C reactive protein

CVD Cardiovascular system diseases

HRV Heart rate variability

mEH Microsomal epoxide hydrolases

N7-GAG N7-(2-carbamoyl-2-hydroxyethyl) guanine

CKD Chronic kidney disease

VOC Organic compounds

AAMA-Sul N-acetyl-3-[(3-amino-3-oxopropyl) sulfinyl]-L-alanine

iso-GAMA N-acetyl-S-(1-carbamoyl-2-hydroxy-ethyl)-L: -cysteine

c-LOD Detection limit

SBP Systolic pressure

DBP Diastolic blood pressure

NASPC N-Acetyl-S-(propionamide)-cysteine

TGF-β1 Plasma transforming growth factors

Authors’ contributions

All authors contributed to the study conception and design. Fang-Fang Zhao: Writing – original draft, Conceptualization, Project administration. Xiao-Li Wang: Data reduction, Project administration. Ya-Ting Lei and Hong-Qiu Li: Literature search, Formal analysis. Investigation. Zhi-Ming Li: Data entering, Methodology. Xiao-Xiao Hao: Investigation, Methodology. Wei-Wei Ma: Investigation, Methodology. Yong-Hui Wu: Investigation, Methodology. Sheng-Yuan Wang: Writing – review & editing. All authors approved the final version.

Funding

This study was supported by grants from the National Natural Science Foundation of China (81803207), Natural Science Foundation of Heilongjiang Province Outstanding Youth project(YQ2021H007).

Availability of data material

This is a systematic review article and its data is extracted from the original articles.

Compliance with ethical standards:

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors that they have no competing interests.

Andačić, Ivana Mandić et al. 2020. ‘Exposure of the Croatian Adult Population to Acrylamide through Bread and Bakery Products’. Food Chemistry 322: 126771.
Bhatnagar, Aruni. 2004. ‘Cardiovascular Pathophysiology of Environmental Pollutants’. American Journal of Physiology. Heart and Circulatory Physiology 286(2): H479-485.
Bjellaas, T. et al. 2005. ‘Determination and Quantification of Urinary Metabolites after Dietary Exposure to Acrylamide’. Xenobiotica; the Fate of Foreign Compounds in Biological Systems 35(10–11): 1003–18.
Bjellaas, Thomas et al. 2007. ‘Urinary Acrylamide Metabolites as Biomarkers for Short-Term Dietary Exposure to Acrylamide’. Food and Chemical Toxicology: An International Journal Published for the British Industrial Biological Research Association 45(6): 1020–26.
Boettcher, Melanie I., Hermann M. Bolt, and Jürgen Angerer. 2006. ‘Acrylamide Exposure via the Diet: Influence of Fasting on Urinary Mercapturic Acid Metabolite Excretion in Humans’. Archives of Toxicology 80(12): 817–19.
Boettcher, Melanie I., Hermann M. Bolt, Hans Drexler, and Jürgen Angerer. 2006. ‘Excretion of Mercapturic Acids of Acrylamide and Glycidyl amide in Human Urine after Single Oral Administration of Deuterium-Labelled Acrylamide’. Archives of Toxicology 80(2): 55–61.
Boettcher, Melanie Isabell et al. 2005. ‘Mercapturic Acids of Acrylamide and Glycidyl amide as Biomarkers of the Internal Exposure to Acrylamide in the General Population’. Mutation Research/Genetic Toxicology and Environmental Mutagenesis 580(1): 167–76.
Boettcher, Melanie Isabell, and Jürgen Angerer. 2005. ‘Determination of the Major Mercapturic Acids of Acrylamide and Glycidyl amide in Human Urine by LC-ESI-MS/MS’. Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences 824(1–2): 283–94.
Boyle, Elizabeth Barksdale et al. 2016. ‘Assessment of Exposure to VOCs among Pregnant Women in the National Children’s Study’. International Journal of Environmental Research and Public Health 13(4): 376.
Calleman, C. J. et al. 1994. ‘Relationships between Biomarkers of Exposure and Neurological Effects in a Group of Workers Exposed to Acrylamide’. Toxicology and Applied Pharmacology 126(2): 361–71.
Calleman, C. J., E. Bergmark, and L. G. Costa. 1990. ‘Acrylamide Is Metabolized to Glycidyl amide in the Rat: Evidence from Hemoglobin Adduct Formation’. Chemical Research in Toxicology 3(5): 406–12.
Chain (CONTAM), EFSA Panel on Contaminants in the Food. 2015. ‘Scientific Opinion on Acrylamide in Food’. EFSA Journal 13(6): 4104.
Chaudhry, Q., J. Cotterill, and R. Watkins. 2006. ‘7 - A Molecular Modelling Approach to Predict the Toxicity of Compounds Generated during Heat Treatment of Foods’. In Acrylamide and Other Hazardous Compounds in Heat-Treated Foods, Woodhead Publishing Series in Food Science, Technology and Nutrition, eds. K. Skog and J. Alexander. Woodhead Publishing, 132–60. https://www.sciencedirect.com/science/article/pii/B9781845690113500070 (August 19, 2022).
Chu, P.-L. et al. 2017. ‘Negative Association between Acrylamide Exposure and Body Composition in Adults: NHANES, 2003-2004’. Nutrition and Diabetes 7(3). https://www.embase.com/search/results?subaction=viewrecord&id=L614762522&from=export.
Chuang, W.h., C.p. Chiu, and B.h. Chen. 2006. ‘Analysis and Formation of Acrylamide in French Fries and Chicken Legs During Frying’. Journal of Food Biochemistry 30(5): 497–507.
Chung, Chi-Jung et al. 2020. ‘Relationships among Cigarette Smoking, Urinary Biomarkers, and Urothelial Carcinoma Risk: A Case-Control Study’. Environmental Science and Pollution Research International 27(34): 43177–85.
Cresteil, T. 1998. ‘Onset of Xenobiotic Metabolism in Children: Toxicological Implications’. Food Additives and Contaminants 15 Suppl: 45–51.
Doroshyenko, Oxana et al. 2009. ‘In Vivo Role of Cytochrome P450 2E1 and Glutathione-S-Transferase Activity for Acrylamide Toxicokinetics in Humans’. Cancer Epidemiology, Biomarkers & Prevention: A Publication of the American Association for Cancer Research, Cosponsored by the American Society of Preventive Oncology 18(2): 433–43.
Duale, Nur et al. 2009. ‘Biomarkers of Human Exposure to Acrylamide and Relation to Polymorphisms in Metabolizing Genes’. Toxicological Sciences: An Official Journal of the Society of Toxicology 108(1): 90–99.
Duke, T.J., P.S. Ruestow, and G.M. Marsh. 2018. ‘The Influence of Demographic, Physical, Behavioral, and Dietary Factors on Hemoglobin Adduct Levels of Acrylamide and Glycidyl amide in the General U.S. Population’. Critical reviews in food science and nutrition 58(5): 700–710.
Dybing, E. et al. 2005. ‘Human Exposure and Internal Dose Assessments of Acrylamide in Food’. Food and Chemical Toxicology: An International Journal Published for the British Industrial Biological Research Association 43(3): 365–410.
Eicher, Angela et al. 2020. ‘Exposure to Acrylamide from Home-Cooked Food: Fried Potatoes (Rösti) in Switzerland as an Example’. Food Additives & Contaminants. Part A, Chemistry, Analysis, Control, Exposure & Risk Assessment 37(12): 2061–69.
F Fernández, Sandra et al. 2022. ‘Exposure Assessment of Spanish Lactating Mothers to Acrylamide via Human Biomonitoring’. Environmental Research 203: 111832.
Fennell, Timothy R. et al. 2006. ‘Kinetics of Elimination of Urinary Metabolites of Acrylamide in Humans’. Toxicological Sciences: An Official Journal of the Society of Toxicology 93(2): 256–67.
Fernández, Sandra F. et al. 2022. ‘Risk Assessment of the Exposure of Spanish Children to Acrylamide Using Human Biomonitoring’. Environmental Pollution (Barking, Essex: 1987) 305: 119319.
Freisling, Heinz et al. 2013. ‘Dietary Acrylamide Intake of Adults in the European Prospective Investigation into Cancer and Nutrition Differs Greatly According to Geographical Region’. European Journal of Nutrition 52(4): 1369–80.
Friedman, Mendel. 2003. ‘Chemistry, Biochemistry, and Safety of Acrylamide. A Review’. Journal of Agricultural and Food Chemistry 51(16): 4504–26.
Frigerio, Gianfranco et al. 2020. ‘Urinary Biomonitoring of Subjects with Different Smoking Habits. Part I: Profiling Mercapturic Acids’. Toxicology Letters 327: 48–57.
Fuhr, Uwe et al. 2006. ‘Toxicokinetics of Acrylamide in Humans after Ingestion of a Defined Dose in a Test Meal to Improve Risk Assessment for Acrylamide Carcinogenicity’. Cancer Epidemiology, Biomarkers & Prevention: A Publication of the American Association for Cancer Research, Cosponsored by the American Society of Preventive Oncology 15(2): 266–71.
Gao, Jie et al. 2016. ‘Dietary Exposure of Acrylamide from the Fifth Chinese Total Diet Study’. Food and Chemical Toxicology: An International Journal Published for the British Industrial Biological Research Association 87: 97–102.
Garey, Joan, and Merle G. Paule. 2007. ‘Effects of Chronic Low-Dose Acrylamide Exposure on Progressive Ratio Performance in Adolescent Rats’. Neurotoxicology 28(5): 998–1002.
Goerke, Katharina et al. 2019. ‘Biomonitoring of Nutritional Acrylamide Intake by Consumers without Dietary Preferences as Compared to Vegans’. Archives of Toxicology 93(4): 987–96.
Hagmar, L. et al. 2001. ‘Health Effects of Occupational Exposure to Acrylamide Using Hemoglobin Adducts as Biomarkers of Internal Dose’. Scandinavian Journal of Work, Environment & Health 27(4): 219–26.
Hartmann, Eva C. et al. 2008. ‘Hemoglobin Adducts and Mercapturic Acid Excretion of Acrylamide and Glycidyl amide in One Study Population’. Journal of Agricultural and Food Chemistry 56(15): 6061–68.
———. 2009. ‘N-Acetyl-S-(1-Carbamoyl-2-Hydroxy-Ethyl)-L-Cysteine (Iso-GAMA) a Further Product of Human Metabolism of Acrylamide: Comparison with the Simultaneously Excreted Other Mercaptuic Acids’. Archives of Toxicology 83(7): 731–34.
He, F. S. et al. 1989. ‘Neurological and Electroneuromyographic Assessment of the Adverse Effects of Acrylamide on Occupationally Exposed Workers’. Scandinavian Journal of Work, Environment & Health 15(2): 125–29.
Heudorf, Ursel, Eva Hartmann, and Jürgen Angerer. 2009. ‘Acrylamide in Children--Exposure Assessment via Urinary Acrylamide Metabolites as Biomarkers’. International Journal of Hygiene and Environmental Health 212(2): 135–41.
Hj, Clewell et al. 2002. ‘Review and Evaluation of the Potential Impact of Age- and Gender-Specific Pharmacokinetic Differences on Tissue Dosimetry’. Critical reviews in toxicology 32(5). https://pubmed.ncbi.nlm.nih.gov/12389868/ (August 19, 2022).
Hogervorst, Janneke G. et al. 2007. ‘A Prospective Study of Dietary Acrylamide Intake and the Risk of Endometrial, Ovarian, and Breast Cancer’. Cancer Epidemiology, Biomarkers & Prevention: A Publication of the American Association for Cancer Research, Cosponsored by the American Society of Preventive Oncology 16(11): 2304–13.
Hsu, Chien-Ning et al. 2020. ‘Association between Acrylamide Metabolites and Cardiovascular Risk in Children With Early Stages of Chronic Kidney Disease’. International Journal of Molecular Sciences 21(16): E5855.
Huang, Chih-Chun Jean et al. 2007. ‘Analysis of Urinary N-Acetyl-S-(Propionamide)-Cysteine as a Biomarker for the Assessment of Acrylamide Exposure in Smokers’. Environmental Research 104(3): 346–51.
———. 2015. ‘Potential Association of Urinary N7-(2-Carbamoyl-2-Hydroxyethyl) Guanine with Dietary Acrylamide Intake of Smokers and Nonsmokers’. Chemical Research in Toxicology 28(1): 43–50.
Huang, Yu-Fang et al. 2011. ‘Association of CYP2E1, GST and MEH Genetic Polymorphisms with Urinary Acrylamide Metabolites in Workers Exposed to Acrylamide’. Toxicology Letters 203(2): 118–26.
IARC. 1994. ‘IARC Monographs on the Evaluation of Carcinogenic Risks to Humans Volume 60’. Some Industrial Chemicals. https://publications.iarc.fr/Book-And-Report-Series/Iarc-Monographs-On-The-Identification-Of-Carcinogenic-Hazards-To-Humans/Some-Industrial-Chemicals-1994.
Ji, Kyunghee et al. 2013. ‘Urinary Levels of N-Acetyl-S-(2-Carbamoylethyl)-Cysteine (AAMA), an Acrylamide Metabolite, in Korean Children and Their Association with Food Consumption’. The Science of the Total Environment 456–457: 17–23.
Johner, S. A., H. Boeing, M. Thamm, and T. Remer. 2015. ‘Urinary 24-h Creatinine Excretion in Adults and Its Use as a Simple Tool for the Estimation of Daily Urinary Analyte Excretion from Analyte/Creatinine Ratios in Populations’. European Journal of Clinical Nutrition 69(12): 1336–43.
Joint FAO/WHO Expert Committee on Food Additives. 2006. ‘Evaluation of Certain Food Contaminants’. World Health Organization Technical Report Series 930: 1–99, back cover.
Kawahara, Junko et al. 2019. ‘Dietary Exposure to Acrylamide in a Group of Japanese Adults Based on 24-Hour Duplicate Diet Samples’. Food Additives & Contaminants. Part A, Chemistry, Analysis, Control, Exposure & Risk Assessment 36(1): 15–25.
Kenwood, Brandon M. et al. 2022. ‘Cigarette Smoking Is Associated with Acrylamide Exposure among the U.S. Population: NHANES 2011-2016’. Environmental Research 209: 112774.
Kim, Seong-Min et al. 2015. ‘Modified Lipoproteins by Acrylamide Showed More Atherogenic Properties and Exposure of Acrylamide Induces Acute Hyperlipidemia and Fatty Liver Changes in Zebrafish’. Cardiovascular Toxicology 15(4): 300–308.
Kirman, Christopher R. et al. 2003. ‘A Physiologically Based Pharmacokinetic Model for Acrylamide and Its Metabolite, Glycidyl amide, in the Rat’. Journal of Toxicology and Environmental Health. Part A 66(3): 253–74.
Kito, Kumiko et al. 2020. ‘Dietary Acrylamide Intake and the Risk of Pancreatic Cancer: The Japan Public Health Center-Based Prospective Study’. Nutrients 12(11): E3584.
Klaunig, James E. 2008. ‘Acrylamide Carcinogenicity’. Journal of Agricultural and Food Chemistry 56(15): 5984–88.
Knudsen, N. et al. 2000. ‘Age- and Sex-Adjusted Iodine/Creatinine Ratio. A New Standard in Epidemiological Surveys? Evaluation of Three Different Estimates of Iodine Excretion Based on Casual Urine Samples and Comparison to 24 h Values’. European Journal of Clinical Nutrition 54(4): 361–63.
Kopp, Eva K., Maximilian Sieber, Marco Kellert, and Wolfgang Dekant. 2008. ‘Rapid and Sensitive HILIC-ESI-MS/MS Quantitation of Polar Metabolites of Acrylamide in Human Urine Using Column Switching with an Online Trap Column’. Journal of Agricultural and Food Chemistry 56(21): 9828–34.
Kopp, Eva Katharina, and Wolfgang Dekant. 2009. ‘Toxicokinetics of Acrylamide in Rats and Humans Following Single Oral Administration of Low Doses’. Toxicology and Applied Pharmacology 235(2): 135–42.
Lee, Jin Heon, Kee Jae Lee, Ryoungme Ahn, and Hee Sook Kang. 2014. ‘Urinary Concentrations of Acrylamide (AA) and N-Acetyl-S-(2-Carbamoylethyl)-Cysteine (AAMA) and Associations with Demographic Factors in the South Korean Population’. International Journal of Hygiene and Environmental Health 217(7): 751–57.
Liao, Kai-Wei et al. 2022. ‘Associating Acrylamide Internal Exposure with Dietary Pattern and Health Risk in the General Population of Taiwan’. Food Chemistry 374: 131653.
Louro, Henriqueta et al. 2019. ‘Human Biomonitoring in Health Risk Assessment in Europe: Current Practices and Recommendations for the Future’. International Journal of Hygiene and Environmental Health 222(5): 727–37.
Mage, David T. et al. 2004. ‘Estimating Pesticide Dose from Urinary Pesticide Concentration Data by Creatinine Correction in the Third National Health and Nutrition Examination Survey (NHANES-III)’. Journal of Exposure Analysis and Environmental Epidemiology 14(6): 457–65.
Mage, David T., Ruth H. Allen, and Anuradha Kodali. 2008. ‘Creatinine Corrections for Estimating Children’s and Adult’s Pesticide Intake Doses in Equilibrium with Urinary Pesticide and Creatinine Concentrations’. Journal of Exposure Science & Environmental Epidemiology 18(4): 360–68.
Mathias, Patricia I., and Clayton B’Hymer. 2014. ‘A Survey of Liquid Chromatographic-Mass Spectrometric Analysis of Mercapturic Acid Biomarkers in Occupational and Environmental Exposure Monitoring’. Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences 964: 136–45.
Mathias, Patricia I., and Clayton B’hymer. 2016. ‘Mercapturic Acids: Recent Advances in Their Determination by Liquid Chromatography/Mass Spectrometry and Their Use in Toxicant Metabolism Studies and in Occupational and Environmental Exposure Studies’. Biomarkers: Biochemical Indicators of Exposure, Response, and Susceptibility to Chemicals 21(4): 293–315.
Miller, M. J., D. E. Carter, and I. G. Sipes. 1982. ‘Pharmacokinetics of Acrylamide in Fisher-334 Rats’. Toxicology and Applied Pharmacology 63(1): 36–44.
Mojska, Hanna et al. 2016. ‘Estimation of Exposure to Dietary Acrylamide Based on Mercapturic Acids Level in Urine of Polish Women Post Partum and an Assessment of Health Risk’. Journal of Exposure Science & Environmental Epidemiology 26(3): 288–95.
———. 2020. ‘Are AAMA and GAMA Levels in Urine after Childbirth a Suitable Marker to Assess Exposure to Acrylamide from Passive Smoking during Pregnancy?-A Pilot Study’. International Journal of Environmental Research and Public Health 17(20): E7391.
Mojska, Hanna, Iwona Gielecińska, and Andrzej Cendrowski. 2016. ‘Acrylamide Content in Cigarette Mainstream Smoke and Estimation of Exposure to Acrylamide from Tobacco Smoke in Poland’. Annals of agricultural and environmental medicine: AAEM 23(3): 456–61.
Moorman, William J. et al. 2012. ‘Occupational Exposure to Acrylamide in Closed System Production Plants: Air Levels and Biomonitoring’. Journal of Toxicology and Environmental Health. Part A 75(2): 100–111.
Mottram, Donald S., Bronislaw L. Wedzicha, and Andrew T. Dodson. 2002. ‘Acrylamide Is Formed in the Maillard Reaction’. Nature 419(6906): 448–49.
Nagata, C. et al. 2015. ‘Associations of Acrylamide Intake with Circulating Levels of Sex Hormones and Prolactin in Premenopausal Japanese Women’. Cancer Epidemiology Biomarkers and Prevention 24(1): 249–54.
Obón-Santacana, Mireia et al. 2016. ‘Acrylamide and Glycidyl amide Hemoglobin Adducts and Epithelial Ovarian Cancer: A Nested Case–Control Study in Nonsmoking Postmenopausal Women from the EPIC Cohort’. Cancer Epidemiology, Biomarkers & Prevention 25(1): 127–34.
Ogawa, Bunichiro et al. 2011. ‘Disruptive Neuronal Development by Acrylamide in the Hippocampal Dentate Hilus after Developmental Exposure in Rats’. Archives of Toxicology 85(8): 987–94.
Ohira, Shin-ichi, Andrea B. Kirk, Jason V. Dyke, and Purnendu K. Dasgupta. 2008. ‘Creatinine Adjustment of Spot Urine Samples and 24 h Excretion of Iodine, Selenium, Perchlorate, and Thiocyanate’. Environmental Science & Technology 42(24): 9419–23.
Pedersen, Marie, Efstathios Vryonidis, Andrea Joensen, and Margareta Törnqvist. 2022. ‘Hemoglobin Adducts of Acrylamide in Human Blood - What Has Been Done and What Is Next?’ Food and Chemical Toxicology: An International Journal Published for the British Industrial Biological Research Association 161: 112799.
Remer, Thomas, Annette Neubert, and Christiane Maser-Gluth. 2002. ‘Anthropometry-Based Reference Values for 24-h Urinary Creatinine Excretion during Growth and Their Use in Endocrine and Nutritional Research’. The American Journal of Clinical Nutrition 75(3): 561–69.
Renwick, A. G., J. L. Dorne, and K. Walton. 2000. ‘An Analysis of the Need for an Additional Uncertainty Factor for Infants and Children’. Regulatory toxicology and pharmacology: RTP 31(3): 286–96.
Rietjens, Ivonne M. C. M. et al. 2018. ‘Exposure Assessment of Process-Related Contaminants in Food by Biomarker Monitoring’. Archives of Toxicology 92(1): 15–40.
Ruenz, Meike, Tamara Bakuradze, Gerhard Eisenbrand, and Elke Richling. 2016. ‘Monitoring Urinary Mercapturic Acids as Biomarkers of Human Dietary Exposure to Acrylamide in Combination with Acrylamide Uptake Assessment Based on Duplicate Diets’. Archives of Toxicology 90(4): 873–81.
Schwedler, Gerda et al. 2021. ‘Benzene Metabolite SPMA and Acrylamide Metabolites AAMA and GAMA in Urine of Children and Adolescents in Germany - Human Biomonitoring Results of the German Environmental Survey 2014-2017 (GerES V)’. Environmental Research 192: 110295.
Segerbäck, D. et al. 1995. ‘Formation of N-7-(2-Carbamoyl-2-Hydroxyethyl)Guanine in DNA of the Mouse and the Rat Following Intraperitoneal Administration of [14C]Acrylamide’. Carcinogenesis 16(5): 1161–65.
Smith, Danielle M. et al. 2021. ‘Exposure to Nicotine and Toxicants Among Dual Users of Tobacco Cigarettes and E-Cigarettes: Population Assessment of Tobacco and Health (PATH) Study, 2013-2014’. Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco 23(5): 790–97.
Smith, E. A., and F. W. Oehme. 1991. ‘Acrylamide and Polyacrylamide: A Review of Production, Use, Environmental Fate and Neurotoxicity’. Reviews on Environmental Health 9(4): 215–28.
Stadler, Richard H., and Gabriele Scholz. 2004. ‘Acrylamide: An Update on Current Knowledge in Analysis, Levels in Food, Mechanisms of Formation, and Potential Strategies of Control’. Nutrition Reviews 62(12): 449–67.
Strange, R. C., P. W. Jones, and A. A. Fryer. 2000. ‘Glutathione S-Transferase: Genetics and Role in Toxicology’. Toxicology Letters 112–113: 357–63.
Sumner, S. C., J. P. MacNeela, and T. R. Fennell. 1992. ‘Characterization and Quantitation of Urinary Metabolites of [1,2,3-13C]Acrylamide in Rats and Mice Using 13C Nuclear Magnetic Resonance Spectroscopy’. Chemical Research in Toxicology 5(1): 81–89.
Sumner, Susan C. J. et al. 2003. ‘Acrylamide: A Comparison of Metabolism and Hemoglobin Adducts in Rodents Following Dermal, Intraperitoneal, Oral, or Inhalation Exposure’. Toxicological Sciences: An Official Journal of the Society of Toxicology 75(2): 260–70.
Sy, Choi et al. 2019. ‘Association of Urinary Acrylamide Concentration with Lifestyle and Demographic Factors in a Population of South Korean Children and Adolescents’. Environmental science and pollution research international 26(18). https://pubmed.ncbi.nlm.nih.gov/31041702/ (August 19, 2022).
Tanaka, T. et al. 2002. ‘A Simple Method to Estimate Populational 24-h Urinary Sodium and Potassium Excretion Using a Casual Urine Specimen’. Journal of Human Hypertension 16(2): 97–103.
Twaddle, Nathan C. et al. 2004. ‘Determination of Acrylamide and Glycidyl amide Serum Toxicokinetics in B6C3F1 Mice Using LC–ES/MS/MS’. Cancer Letters 207(1): 9–17.
Urban, Michael et al. 2006. ‘Urinary Mercapturic Acids and a Hemoglobin Adduct for the Dosimetry of Acrylamide Exposure in Smokers and Nonsmokers’. Inhalation Toxicology 18(10): 831–39.
Vera, Manel et al. 2018. ‘Antioxidant and Anti-Inflammatory Strategies Based on the Potentiation of Glutathione Peroxidase Activity Prevent Endothelial Dysfunction in Chronic Kidney Disease’. Cellular Physiology and Biochemistry: International Journal of Experimental Cellular Physiology, Biochemistry, and Pharmacology 51(3): 1287–1300.
Vesper, Hubert W. et al. 2010. ‘Exposure of the U.S. Population to Acrylamide in the National Health and Nutrition Examination Survey 2003-2004’. Environmental Health Perspectives 118(2): 278–83.
Vought, R. L., and W. T. London. 1964. ‘IODINE INTAKE AND EXCRETION IN HEALTHY NONHOSPITALIZED SUBJECTS’. The American Journal of Clinical Nutrition 15: 124–32.
Vought, R. L., W. T. London, L. Lutwak, and T. D. Dublin. 1963. ‘RELIABILITY OF ESTIMATES OF SERUM INORGANIC IODINE AND DAILY FECAL AND URINARY IODINE EXCRETION FROM SINGLE CASUAL SPECIMENS’. The Journal of Clinical Endocrinology and Metabolism 23: 1218–28.
Walker, Katherine et al. 2007. ‘Approaches to Acrylamide Physiologically Based Toxicokinetic Modeling for Exploring Child-Adult Dosimetry Differences’. Journal of Toxicology and Environmental Health. Part A 70(24): 2033–55.
Wang, Bin, Weihong Qiu, et al. 2020. ‘Acrylamide Exposure and Oxidative DNA Damage, Lipid Peroxidation, and Fasting Plasma Glucose Alteration: Association and Mediation Analyses in Chinese Urban Adults’. Diabetes Care 43(7): 1479–86.
Wang, Bin, Man Cheng, et al. 2020. ‘Exposure to Acrylamide and Reduced Heart Rate Variability: The Mediating Role of Transforming Growth Factor-β’. Journal of Hazardous Materials 395: 122677.
Wang, Bin et al. 2021. ‘Acrylamide Exposure and Pulmonary Function Reduction in General Population: The Mediating Effect of Systemic Inflammation’. The Science of the Total Environment 778: 146304.
———. 2022. ‘Acrylamide Exposure Increases Cardiovascular Risk of General Adult Population Probably by Inducing Oxidative Stress, Inflammation, and TGF-Β1: A Prospective Cohort Study’. Environment International 164: 107261.
Wang, Hao et al. 2010. ‘Reproductive Toxicity of Acrylamide-Treated Male Rats’. Reproductive Toxicology (Elmsford, N.Y.) 29(2): 225–30.
Wang, Sheng-Yuan et al. 2020. ‘A Urinary Metabolomic Study from Subjects after Long-Term Occupational Exposure to Low Concentration Acrylamide Using UPLC-QTOF/MS’. Archives of Biochemistry and Biophysics 681: 108279.
Wang, Wei et al. 2018. ‘Anthropometry-Based 24-h Urinary Creatinine Excretion Reference for Chinese Children’. PloS One 13(5): e0197672.
Wirfält, E. et al. 2008. ‘Associations between Estimated Acrylamide Intakes, and Hemoglobin AA Adducts in a Sample from the Malmö Diet and Cancer Cohort’. European Journal of Clinical Nutrition 62(3): 314–23.
Yousef, M. I., and F. M. El-Demerdash. 2006. ‘Acrylamide-Induced Oxidative Stress and Biochemical Perturbations in Rats’. Toxicology 219(1–3): 133–41.
Zha, Ling et al. 2020. ‘Dietary Acrylamide Intake and the Risk of Liver Cancer: The Japan Public Health Center-Based Prospective Study’. Nutrients 12(9): E2503.
Zhang, Yu et al. 2015. ‘Comprehensive Profiling of Mercapturic Acid Metabolites from Dietary Acrylamide as Short-Term Exposure Biomarkers for Evaluation of Toxicokinetics in Rats and Daily Internal Exposure in Humans Using Isotope Dilution Ultra-High Performance Liquid Chromatography Tandem Mass Spectrometry’. Analytica Chimica Acta 894: 54–64.

Highlights.docx

Download PDF

Journal Publication

published 17 Jul, 2023

Read the published version in Environmental Science and Pollution Research →

Editorial decision: Minor Revision
25 Jun, 2023
Reviewers invited by journal
09 Apr, 2023
Reviewers agreed at journal
01 Apr, 2023
Editor invited by journal
08 Mar, 2023
Editor assigned by journal
24 Feb, 2023
First submitted to journal
18 Feb, 2023

You are reading this latest preprint version

A systematic review: On the mercaptoacid metabolites of acrylamide, N-Acetyl-S-(2- carbamoylethyl)-L-cysteine.

Status:

Journal Publication

Version 1

Abstract

Figures

1. Introduction

2. Search Strategy

3. Results

3.1. Quantification of AAMA levels of acrylamide in the general population

3.2. Possible influencing factors causing AAMA differences

3.2.1. Smoking

3.2.2. Living Country

3.2.3. Age

3.3. Correlation study

4. Discussion

4.1. Urine AAMA as a biomarker of exposure in the short term

4.1.1. Advantages of AAMA over several other mercapturic acid metabolites

4.1.2 Dietary intake of acrylamide in the short term can be deduced from urine AAMA levels

4.1.3 AAMA for urinary metabolites of acrylamide: detectability, accessibility, accuracy

4.2 Effects of various factors on urinary AAMA levels

4.3 Associations of AAMA with various indicators and diseases have been reported

4.4 Research Gaps and Future Needs

5. Conclusions

Abbreviations

Declarations

References

Supplementary Files

Status:

Journal Publication

Version 1