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Abstract

Introduction:

Environmental arsenic contamination is a major toxicological problem worldwide due to its carcinogenic and nephrotoxic potential.

Aim:

The purpose of this observational study was to determine the suspected association between urinary arsenic (uAs) and urinary leucine (or leucyl) aminopeptidase 3 (uLAP₃) to evaluate uLAP₃ as a candidate biomarker of exposure to airborne arsenic.

Materials and Methods:

A total of 918 adults occupationally and/or environmentally exposed to airborne arsenic were enrolled in the study. Baseline information (age; sex; history of smoking; alcohol, fish and seafood consumption) was gathered. Total uAs concentrations [μg/L] of 918 subjects, as well as the sum of arsenic species (ΣiAs) in 259 subjects, were obtained. Urinary LAP₃ was measured by an immune-enzymatic assay using an ELISA kit. Urinary creatinine concentration was assessed with the IB/lAB/1289 research protocol (version II, 2015-09-17). The values of uAs and uLAP₃ were recalculated per unit of creatinine. The association between uAs and uLAP₃ was assessed using a logistic regression model adjusted for confounders.

Results:

The study identified a positive correlation between the logarithm of uAs and the logarithm of uLAP₃ in the study population (r = 0.1737, p < 0.0000) and between urinary creatinine and uLAP₃ concentration not adjusted for creatinine level (r = 0.1871, p < 0.001). In the logistic regression model, there was also an association between increased (≥15 µg/L) uAs and decreased (below the 25th quartile) uLAP₃ [OR uLAP₃ = 1.22 (95% CI 1.03 to 1.44, p < 0.02)].

Conclusions:

These data suggest that urinary LAP₃ may be a potential biomarker of arsenic exposure, which warrants further study.

Keywords

Air pollution arsenic environmental exposure leucyl aminopeptidase 3

Introduction

Environmental arsenic contamination is a relevant toxicological, geochemical and ecological issue worldwide. Millions of people are exposed to arsenic through drinking water, mainly in Taiwan¹ and Bangladesh²; however, exposure to airborne arsenic has been recognized as a local problem in areas with copper mines and copper smelters.³

Arsenic has been associated with the development of cancer,^4,5 kidney damage,⁶ cardiovascular diseases^7,8 and diabetes mellitus.⁹ Ingesting drinking water containing a high concentration of arsenic at is a risk factor for lung cancer; however, it is unclear whether there is such an association in the case of low levels of exposure to arsenic.¹⁰ Consuming drinking water polluted with arsenic has also been found to be a risk factor for basal cell and squamous cell skin cancers, as well as renal, ureteric and bladder cancers.^4,5,11 Less is known about the carcinogenic effects of airborne arsenic. According to World Health Organization (WHO) arsenic guidelines (2019), tobacco smoking is associated with exposure to natural inorganic arsenic. The source of the inorganic arsenic in tobacco is soil and lead arsenate-containing insecticides used in tobacco cultivation.

Kidneys are particularly sensitive to the toxic effects of arsenic that enters the body via both the alimentary and inhalatory routes. Arsenic nephrotoxicity generally depends on the blood arsenic concentration.¹² In subjects chronically exposed to arsenic, toxic and carcinogenic effects may be exerted through oxidative stress and inflammation.^13,14 Oxidative stress is associated with an increase in specific markers, such as urinary isoprostanes, whereas inflammation is associated with an upregulation of tumor necrosis factor-α and interleukin-6.

In humans, leucine aminopeptidases are early markers of nephropathy¹⁵ and cancer.^16
–18 These enzymes are associated with tumor cell proliferation, invasion and angiogenesis. LAP₃ expression is significantly upregulated in hepatocellular carcinoma cells and closely correlates with decreased differentiation, metastasis to lymphatic nodes and a poor prognosis.¹⁷ Overexpression of LAP₃ contributes to the development of human esophageal squamous cell carcinoma.¹⁹ LAP₃ promotes glioma progression by regulating the proliferation, migration and invasion of glioma cells.²⁰ In breast cancer, LAP₃ overexpression plays a crucial role in tumor metastasis.²¹

Leucine (leucyl) aminopeptidases (LAPs) preferentially catalyze the hydrolysis of leucine residues at the N-terminus of peptides and proteins. These enzymes are active in the presence of manganese, magnesium and zinc ions. LAPs have been identified in bacteria, parasites, plants and humans. In several bacterial species, LAP acts as a DNA-binding protein and repressor or activator of operon regulation of virulence-associated genes.¹⁶ LAP from Plasmodium falciparum is being studied as a promising target for novel antimalarials.²² Impaired hydrolysis of RNA and proteins in rice seedlings due to the inhibitory effects of arsenic on RNase and LAP activity has been observed.²³

The established role of arsenic and the suspected involvement of LAPs in carcinogenesis and nephrotoxicity was the rationale for conducting our investigation. The purpose of this observational study was to determine the suspected association between urinary arsenic and urinary LAP₃ and to evaluate LAP₃ as a useful marker of exposure to airborne arsenic in a population residing within a copper smelter impact zone. In this zone, the airborne arsenic concentration exceeded the accepted limit, whereas the concentration of arsenic in drinking water was low.

Material and methods

In 2017, a group of 918 volunteers environmentally exposed to airborne arsenic was enrolled in the study. The inclusion criteria were aged over 18 years and living in a zone in which the arsenic air concentration exceeded the upper limit recommended by European Environment Agency (EEA), i.e. 6 ng/m³. All participants were from a region where the average annual arsenic air concentration was 30.2 ng/m³ in 2017 and 10.04 ng/m³ in 2018, according to the Provincial Inspectorate for Environmental Protection, whereas the arsenic concentration in the drinking water was lower than 10 µg/L. The exclusion criterion was fish, seafood or alcohol consumption in the 4 days preceding blood sample collection to minimize the effects of dietary intake of arsenic on the measured parameters.

Baseline information (age, sex, history of smoking, alcohol consumption, recent fish and seafood consumption) was gathered via a questionnaire. Participants were divided into subgroups based on age, namely, below 40, between 40 and 60 and above 60 years old, as well as smoking habits: current smokers, former smokers and nonsmokers (the reference group). Further subgroup division was based on alcohol consumption, which was defined as regular (at least once a week), occasional (less than once a month) and abstinence (the reference group). Among the 918 people, 15 did not provide information about smoking, 22 about alcohol consumption, and 25 about fish and seafood consumption. Considering the whole sample, the missing data represented less than 2.7% and did not significantly affect the final results.

The study population was divided into two exposure groups: a large group of subjects who were environmentally exposed to arsenic and a small sample of subjects who were exposed to arsenic both environmentally and occupationally. The second group included 79 men who were copper miners or copper smelters, aged 38.3 ± 8.0 years and occupationally exposed to arsenic for at least 10 years.

Given the increasing evidence that urinary arsenic may differ between sexes,²⁴ potential differences between men and females environmentally exposed to arsenic were also explored.

This study was conducted in accordance with the Declaration of Helsinki (1964). Participants provided written, informed consent to participate in the study. The project received a positive opinion from the local ethical committee (No: KB-125/2015). The methodology followed the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) checklist.

Urinary arsenic

The total urinary arsenic (uAs) concentrations [μg/L] in the 918 participants, as well as the sum of arsenic species (ΣiAs), including inorganic arsenic (iAs), monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) [μg/L] of 259 subjects, were measured at the Central Institute of Occupational Medicine (Lodz, Poland) using HPLC-ICP-MS.²⁵

Urinary LAP₃ and creatinine concentrations

Biological samples were collected between September 29, 2017, and December 8, 2017. Urine samples taken in the morning after overnight rest and samples for the determination of arsenic in urine, were simultaneously collected in 10 milliliter tubes with a descriptive code and placed in a freezer at −80°C. Biochemical measurements were performed between January and May 2018. Urinary LAP₃ was measured by an immune-enzymatic assay using an ELISA kit (Wuhan EIAab Science Co., Ltd., Wuhan, China) and a Multimode reader SYNERGY/lX (BioTekSynergy/lX, Vermont, USA). Positive and negative controls were tested to ensure interlaboratory quality control for uLAP₃ determinations. For each set of test samples, a standard curve was constructed according to the manufacturer’s instructions, the target enzyme concentration in each sample was determined in duplicate, and the obtained values were correlated with the curve.

Urinary creatinine (ICD: M37) was measured according to the IB/LAB/1289 research protocol (version II, 2015-09-17), with a reference range 28–217 mg/dL, in an accredited laboratory (PCA No. AM003).

Urinary arsenic and LAP₃ values, expressed in μg/L and μg/mL, respectively, were recalculated per unit of creatinine.

Statistical analysis

Summary statistics were calculated for each variable; means ± SDs or medians and quartiles were calculated for continuous variables, and n (%) was calculated for categorical variables for the whole study population and for each subgroup. A natural logarithmic transformation [ln(x)] was applied to the variables with skewed distributions: uAs and sum iAs+MMA+DMA (ΣuAs). This transformation allowed for the stabilization of variances for parametric model assumptions and reduced the influence of extreme values. Multiple regression analysis was used to assess the effect of urinary arsenic on uLAP₃. Our final logistic regression models were built by the backwards stepwise method and adjusted for sex, age, smoking status, alcohol consumption, and occupational exposure to arsenic. In the first logistic regression step, qualitative and quantitative predictions were defined. The coding of qualitative variables with sigma limitations (quasi-experimental) was performed. Potential predictors were evaluated by logistic regression, a one-factor analysis. A p-value of 0.05 was used as the cutoff to indicate statistical significance. The TIBCO Statistica 13.3 program was used.

Results

The characteristics of the study population are presented in Table 1. The most numerous subgroup in the study was females over the age of 40. The number of participating males was approximately half that of participating females. Seventy-nine men were not only environmentally but also occupationally exposed to arsenic.

Table 1.

Characteristics of the studied population.

Sex	Women (n = 608)	Men (n = 310)
Age (years)	51.9 ± 13.2	53.8 ± 14.9
Number (%) of people according to age:
20–39	115 (18.9)	64 (20.6)
40–59	270 (44.4)	102 (32.9)**
60–82	209 (34.3)	144 (46.4)
Number (%) of people according to smoking habits:
Non-smokers	417 (68.5)	158 (50.9)
Former smokers	103 (16.9)	106 (34.1)*
Current smokers	63 (10.3)	44 (14.1)
Number (%) of people according to alcohol consumption:
Abstainers	420 (69.2)	214 (69.0)
Occasional drinkers	62 (10.1)	38 (12.2)
Regular drinkers	126 (20.7)	56 (18.0)
Number (%) of people according to occupational exposure to arsenic:
Exposed	0 (0)	79 (25.4)
Not exposed	608 (100)	231 (74.5)

*, ** statistically significant differences between groups of men and women; * p < 0.05, ** p < 0.01.

The distribution of urinary creatinine across the study population is presented in Table 2 (group sizes are the same as those in Table 1).

Table 2.

The distribution of urinary creatinine in studied groups.

Urinary creatinine concentration (mg/dL)
Sex:	Women	Men	p
	89.2 ± 57.8	114.3 ± 66.1	0.0000
Age in years
20–39	133.5 ± 68.3	156.1 ± 82.4	0.0486
40–59	90.0 ± 52.0	125.6 ± 59.0	0.0000
60–82	63.9 ± 43.1	86.7 ± 47.3	0.0000
Smoking:
Non-smokers	92.0 ± 59.9	115.1 ± 61.5	0.0000
Former smokers	90.9 ± 62.1	126.1 ± 53.1	0.0028
Current smokers	75.0 ± 10.3	106.9 ± 64.1	0.0001
Alcohol consumption:
Abstainers	89.1 ± 58.5	113.7 ± 68.5	0.0000
Occasional drinkers	94.9 ± 55.4	104.4 ± 53.8	0.4418
Regular drinkers	88.9 ± 55.3	115.7 ± 60.2	0.0052
Occupational exposure to As:
Yes	—	142.0 ± 69.1	—
No	89.2 ± 57.8	105.2 ± 62.6	0.0004

p—the level of statistical significance of the difference between women and men.

The distribution of urinary LAP₃ (uLAP₃) and total urinary arsenic (uAs) values was lognormal. The median uLAP₃ (Q25; Q75) values among 310 males and 608 females environmentally exposed to airborne arsenic were similar, while the median uAs in males were higher than those in females. However, after adjustment for urinary creatinine level, the median uLAP₃ in males was lower than that in females (p < 0.001), whereas the median uAs concentration was similar in both groups (Table 3).

Table 3.

Urinary leucine aminopeptidase 3 (LAP₃) and arsenic (uAs) before and after adjustment for creatinine level.

Sex (number)	uLAP₃: median (Q25; Q75)	uAs: median (Q25; Q75)
Women	0.29 (0.16; 0.54) ng/mL	7.05 (3.75; 17.50) ng/mL
(608)	42.41 (21,48; 85,16) μg/µg creatinine	10.54 (5.24; 22.14) μg/g creatinine
Men	0.25 (0.14; 0.54) ng/mL	8.60 (4.80; 17.80) ng/mL**
(310)	28.05 (14.83; 61.10) μg/µg creatinine***	8.48 (5.00; 18.14) μg/g creatinine

**, *** statistically significant differences between groups of women and men: **p < 0.01, *** p < 0.001.

These differences may be because the mean urine creatinine concentration was approximately 25 mg/dL higher in males than in females (Table 2).

The multiple regression analysis showed a positive correlation between ln(uAs) [μg/g creatinine] and ln(uLAP₃) [μg/µg creatinine] in the entire study group (Figure 1).

Figure 1.

Relationship between logarithm of total urinary arsenic and logarithm of urinary leucine aminopeptidase 3 in the entire studied population (r = 0.1737, F = 28.52, b = 0.1654, t = 5.34, p < 0.0000).

Additionally, a positive linear correlation between ln(uAs) and urinary creatinine was found (Figure 2).

Figure 2.

Correlation between logarithm of urinary total arsenic and urinary creatinine (r = 0.3108, F = 97.9, b = 0.3108, t = 9.89, p < 0.0000).

A total urine arsenic concentration exceeding the upper limit accepted by WHO, i.e. ≥15 μg/L, was observed in 259 people, including 90 males and 169 females. In these males and females, the median (25Q; 75Q) total uAs concentrations were 28.15 (20.5; 66.0) μg/L and 30.4 (20.0; 57.0) μg/L, respectively. The sums of arsenic species (arsenite—iAs^III, arsenate—iAs^V, MMA^V and DMA^V) were measured in these groups. A positive correlation between the logarithm of the sum of arsenic species ln(ΣAs) and ln(uLAP₃) was observed (Figure 3).

Figure 3.

Relationship between logarithm of the sum of urinary arsenic species (lgΣuAs) and logarithm of uLAP₃ in people with total arsenic urine concentration exceeding the upper norm accepted by WHO (r = 0.2256, F = 13.57, df = 1.25, b = 0.2256, p < 0.001).

In the entire study population, uLAP₃ [μg/µg of creatinine] was positively correlated with age (Spearman’s rho = 0.2671; r = 0.14805, p < 0.001). There was a gradual increase in uLAP₃ with age in both males and females as well as smokers and nonsmokers (Table 4). No relationship between age and uLAP₃ expression in ng/mL was found (r = −0.0148, p > 0.05). This discrepancy was probably caused by the reduction in urinary creatinine concentration with age (Table 2).

Table 4.

Urinary LAP₃ (uLAP₃) in smokers vs non-smokers exposed to airborne arsenic.

	Number of smokers	Mean ± SD	Number of non-smokers	Mean ± SD	p
	Number of smokers	uLAP₃ (µg/µg of creatinine) in smokers	Number of non-smokers	uLAP₃ (µg/µg of creatinine) in non-smokers	p
Population exposed to airborne arsenic (men and women)	107	65.7 ± 130.1	796	73.5 ± 123.1	0.5431
Women exposed to airborne arsenic	64	59.1 ± 66.2	529	79.7 ± 127.5	0.3659
aged < 40	12	20.7 ± 11.3	109	51.3 ± 81.9	0.1314
aged 40–59	34	59.3 ± 48.0	232	67.3 ± 80.2	0.5016
aged ≥ 60	18	84.4 ± 99.8	188	102.9 ± 122.1	0.3471
Men exposed to airborne arsenic	43	75.6 ± 189.7	267	61.2 ± 113.1	0.4817
aged < 40	17	27.3 ± 54.7	50	30.5 ± 25.0	0.8621
aged 40–59	14	47.0 ± 77.7	87	50.5 ± 70.5	0.8714
aged ≥ 60	12	177.4 ± 331.	130	80.3 ± 148.5	0.5791
occupationally exposed to arsenic	17	15.7 ± 11.8	62	36.5 ± 41.5	0.0458

Abbreviations: p—the level of statistical significance of the difference between smokers and non-smokers; SD—standard deviation; uLAP₃—urinary leucine aminopeptidase 3.

The effect of cigarette smoking on uLAP₃ concentration was generally not statistically significant. Lower uLAP₃ concentrations were found in smokers than in nonsmokers, except for males over 60 years old (Table 4). In the entire study population, there were no significant differences in uLAP₃ between nonsmokers (N) and former smokers (F). Both nonsmokers and former smokers had higher uLAP₃ concentrations than current smokers (S) (Figure 4). The urinary creatinine concentration was only slightly higher in smokers than in nonsmokers (105.1 ± 60.9 mg/dL vs 98.4 ± 63.2 mg/dL, respectively, ns).

Figure 4.

Urinary LAP3 concentration in non-smokers (N), past-smokers (P) and current smokers (S). Statistical differences in Kruskal-Wallis test, * p < 0.05.

In males, another LAP₃-modifying factor was occupational exposure to arsenic. Urinary LAP₃ was lower (p < 0.001) in the 79 males occupationally exposed to arsenic than in the 231 nonexposed males (32.0 ± 38.1 and 74.5 ± 142.9 μg/µg creatinine, respectively).

The urinary arsenic concentration in the group of any smokers was higher than that in the group of nonsmokers, but the difference was not significant (p > 0.05). There were also no significant difference in arsenic concentration between smokers and nonsmokers in the group of workers occupationally exposed to As (Table 5).

Table 5.

Urinary arsenic (uAs) in smokers vs non-smokers exposed to airborne arsenic.

	Number of smokers	Mean ± SD uAs (µg/µg of creatinine) in smokers	Number of non-smokers	Mean ± SD uAs (µg/µg of creatinine) in non-smokers	p
Population exposed to airborne arsenic (men and women)	105	33.6 ± 90.7	783	23.3 ± 45.3	0.4090
Women exposed to airborne arsenic	62	31.3 ± 105.7	517	24.7 ± 49.0	0.0902
aged < 40	12	20.2 ± 39.5	109	16.9 ± 34.1	0.3833
aged 40–59	33	14.1 ± 15.2	221	26.5 ± 50.4	0.1300
aged ≥ 60	17	72.7 ± 196.3	187	27.3 ± 54.4	0.6642
Men exposed to airborne arsenic	43	36.8 ± 64.2	263	20.5 ± 37.0	0.3883
aged < 40	17	22.5 ± 59.2	49	13.7 ± 25.4	0.7492
aged 40–59	14	33.0 ± 34.3	85	23.0 ± 49.5	0.0605
aged ≥ 60	12	62.5 ± 91.0	129	21.4 ± 30.5	0.1120
occupationally exposed to arsenic	17	46.5 ± 68.0	62	21.5 ± 45.6	0.6152

Abbreviations: p—the level of statistical significance of the difference between smokers and non-smokers; SD—standard deviation; uAs—urinary arsenic.

However, the multivariate analysis of variance showed a significant interaction (p < 0.05) between sex, smoking and uAs impacting uLAP₃ [β = 0.1311; 95% confidence interval (CI), 1.71–26.81]. Smoking males with normal urine arsenic concentrations had higher uLAP₃ levels than nonsmoking males, whereas smoking males with elevated (≥15 µg/L) uAs had lower uLAP₃ levels than nonsmokers (Figure 5).

Figure 5.

Interaction between sex, smoking and total urinary arsenic in the study population.

Alcohol consumption had no significant effect on uLAP₃ or uAs concentrations. The urinary LAP₃ concentrations were 64.9 ± 122.3 μg/µg creatinine in occasional drinkers (n = 99), 73.9 ± 114.1 μg/µg creatinine in regular drinkers (n = 182) and 72.9 ± 124.2 μg/µg creatinine in abstainers (n = 635). The mean uAs concentrations were 25.2 ± 55.2 μg/g creatinine in occasional drinkers, 24.4 ± 54.2 μg/g creatinine in regular drinkers and 24.9 ± 56.3 μg/g creatinine in abstainers.

In all the studied subjects (n = 918), the uLAP₃ concentration expressed in ng/mL increased linearly with urinary creatinine concentration (r = 0.1871, p < 0.001), Figure 6.

Figure 6.

Correlation between urinary creatinine concentration and uLAP₃ (r = 0.1871, F = 35.06, b = 0.1871, t = 5.92, p < 0.0000).

Multiple logistic regression model

A multiple logistic regression model was constructed to determine whether there were significant associations of normal and abnormally high (≥15 μg/L) total urinary arsenic (a qualitative predictor) with an increased concentration of uLAP₃ as the dependent variable. For further statistical analyses, the value of the 75th quartile (Q75) for uLAP₃ (0.54 ng/mL = 72 μg/µg creatinine) was adopted as the cutoff point. Values higher than the Q75 were considered elevated in the study population. The influence of confounders such as sex, age, smoking, alcohol consumption, occupational exposure to arsenic and urinary creatinine was taken into account.

In the total study population exposed to airborne arsenic, a significant association between urinary creatinine and increased uLAP₃ was observed [OR_uLAP3 = 1.020 (95% CI 1.016 to 1.024; p < 0.001)]. Creatinine was also associated with increased uAs [OR_creatinine = 1.006 (95% CI 1.004 to 1.009; p < 0.001)].

In the logistic regression model, an association between normal (lower than 15 μg/L) urinary arsenic and elevated urinary leucine aminopeptidase 3 was shown [OR_uLAP3 = 1.33 (95% CI 1.11 to 1.59), p = 0.0017].

The odds ratio for the association between elevated uAs (≥15 μg/L) and increased uLAP₃ (OR_uLAP3) was 0.73 (95% CI 0.60 to 0.88, p < 0.001). The proportions of people with elevated uLAP₃ were 47/259 (18.1%) in the group with elevated uAs and 186/659 (28.2%) in the group with normal uAs.

In the next step, a logistic regression model using uLAP₃ values below the 25th quartile (Q25) as the dependent variable was constructed. Urinary LAP₃ values lower than the Q25 (0.16 ng/ml = 18,9 μg/µg creatinine) were observed in 242 people (133 females and 109 males), with a mean concentration of 0.11 ± 4.52 ng/mL. There was an association between increased uAs (≥15 μg/L) and decreased (below Q25) uLAP₃ [OR_uLAP3 = 1.22 (95% CI 1.03 to 1.44, p < 0.02)].

Discussion

In this study, an association between kidney function (assessed on the basis of urinary creatinine concentration) and urinary arsenic was shown in the population environmentally exposed to airborne arsenic. Moreover, in people with normal urinary arsenic levels (< 15 μg/L), a positive relationship between uAs and uLAP₃ was found.

Urinary arsenic mainly indicates recent exposure to inorganic arsenic. Most clinical studies on inorganic arsenic and renal outcomes have focused on proteinuria, showing that exposure to both high and low arsenic levels is associated with increased proteinuria.⁶ The nephrotoxic effect of arsenic had also been demonstrated in experimental studies.^26,27 Due to high metabolic activity, the microsomal fraction of the brush border in proximal tubule cells is the part of the nephron that is most susceptible to toxic damage.^28,29 Leucine aminopeptidases are kidney brush border enzymes. Urinary levels of these enzymes indicate damage to the microsomal or membrane fraction.³⁰ In many studies, urinary leucine aminopeptidase was identified as a sensitive indicator of early renal damage.^15,31,32

In our study, an increase in uLAP₃ was correlated with an increase in total arsenic as well as the sum of arsenic species. It remains unclear whether the relationship between uAs and uLAP₃ results from the direct effect of arsenic on proximal tubule cells and/or from the indirect effect on other parts of the nephron, such as glomeruli. The latter is supported by the observation of a significant association between creatinine and increased uLAP₃ as well as between creatinine and increased uAs in the multiple logistic regression model. Since impaired glomerular filtration is the most likely cause of creatinine increase, the existence of these associations could indicate complex nephron dysfunction.

Based on our research, we concluded that the determination of urinary LAP₃ together with urinary creatinine may be useful in the assessment of kidney function in populations exposed to airborne arsenic. One of the key findings was that in all the studied subjects, the uLAP₃ concentration expressed in ng/mL increased linearly with the urinary creatinine concentration. Additionally, an association between creatinine and increased uLAP₃ was shown in the logistic regression model. This indicates a significant influence of creatinine level on uLAP₃. This relationship is clearly visible in the analysis of uLAP₃ by subject age; decreases in creatinine levels due to age were accompanied by increases in the uLAP₃ values in both males and females. However, this was observed for only uLAP₃ values expressed in nanograms per microgram of creatinine; the uLAP₃ values expressed in nanograms per milliliter of urine were not influenced by age. As urinary creatinine and uLAP₃ increased together with urinary arsenic, nephron dysfunction was most likely caused by arsenic exposure.

Similar to other authors,³³ we observed sex differences in urinary excretion of LAP₃. After adjustment for creatinine level, uLAP₃ was higher in females than in males. This may be due to lower urinary creatinine levels in females than in males, resulting in an increased uLAP₃/creatinine quotient.

The relationship between smoking and uLAP₃ seems to be ambiguous and depends on sex. Among normo-arsenic-exposed females, uLAP₃ levels were lower in smokers than in nonsmokers, whereas among normo-arsenic-exposed older males, uLAP3 levels were higher in smokers than in nonsmokers. The interaction between smoking, urinary arsenic and sex may impact the uLAP₃ concentration (Figure 5), explaining these differences. This observation is in alignment with the results from another study, which demonstrated that an interaction between sex and smoking influenced the risk of bladder cancer, and differences in arsenic exposure effects in males and females were noted.³⁴ In a different study, a positive interaction between smoking and urinary arsenic, affecting the risk of lung cancer, was shown.³⁵

In recent years, there has been increasing interest in the role of leucine aminopeptidase 3 in the neoplastic process. LAP₃ is involved in pro-oxidative, inflammatory and proliferative processes.^14,15 LAP₃ overexpression is a known predictor of various human malignancies, e.g. acute promyelocytic leukemia,³⁶ ovarian cancer,¹⁸ breast cancer,²¹ prostate cancer³⁷ and hepatocellular carcinoma.¹⁷ Novel LAP₃ inhibitors are being investigated as potential agents in cancer therapy.

It should be noted that uLAP₃ below the Q25, observed in 242 (26%) people, was associated with elevated uAs (≥15 μg/L) in our study. This association between elevated uAs and decreased uLAP₃ may warrant further research.

Why exposure to arsenic, a known carcinogen,³⁵ is associated with low urinary levels of LAP₃, as LAP₃ normally increases in cancer cells and tissues, remains unclear. Inhibition of LAP₃ by arsenic could explain the antitumor effect of arsenic in some proliferative diseases. Arsenic has long been used in the treatment of leukemia. Currently, research is focused on both the carcinogenic and anticancer effects of inorganic arsenic and its methylated metabolites.^36,38

Our study has several limitations. First, detailed data on participants’ lifestyles and health statuses were missing. Second, while urinary arsenic species are the recommended biological indicators of exposure to inorganic arsenic rather than total urinary arsenic species, they were measured only in 26% of the total study population. Moreover, although urinary arsenic concentration is a result of short-term exposure and therefore probably sensitive to considerable fluctuation, it was measured only once in the studied subjects, and its variability over time was not assessed.

Despite these weaknesses, we believe that urinary leucine aminopeptidase 3 could be a potential biomarker of arsenic exposure. Although this study did not provide evidence of arsenic nephrotoxicity, the positive relationship between urinary excretion of arsenic and uLAP₃ in normo-arsenic-exposed subjects may indicate proximal tubular dysfunction. The observed association between elevated uAs and decreased uLAP₃ warrants further research.

Conclusions

The results of our study provide evidence that urinary LAP₃ is associated with the excretion of arsenic in urine. Establishing the role of LAP₃ in urine as a biomarker of arsenic exposure should be the subject of future research.

Footnotes

Acknowledgements

Results of total urinary arsenic concentrations as well as sum of arsenic species were provided courtesy of The Copper Health Centre.

Data availability statement

The detailed data can be made available at the Editor’s request.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Wroclaw Medical University (Grant Number KO/68/U/17).

ORCID iD

Anna Skoczynska

References

Liang

Chien

Jang

, et al. Spatial analysis of human health risk due to arsenic exposure through drinking groundwater in Taiwan’s Pingtung plain. Int J Environ Res Public Health 2017; 14: 81.

Smith

Lingas

Rahman

.Contamination of drinking water by arsenic in Bangladesh: a public health emergency. Bull World Health Organ 2000; 83: 177–186.

Air quality in Europe—2015 report. European Environment Agency. EEA Report No. 5/2015, http://www.eea.europa.eu/publications/air-quality-in-europe-2015.

Karagas

Tosteson

Blum

, et al. Design of an epidemiologic study of drinking water arsenic exposure and skin and bladder cancer risk in a U.S. population. Environ Health Perspect 1998; 106: 1047–1050.

Saint-Jacques

Brown

Nauta

, et al.Estimating the risk of bladder and kidney cancer from exposure to low-levels of arsenic in drinking water, Nova Scotia, Canada. Environ Int 2018; 110: 95–104.

Zheng

Umans

Yeh

, et al. The association of urine arsenic with prevalent and incident chronic kidney disease: evidence from the strong heart study. Epidemiology 2015; 26: 601–612.

Farzan

Chen

Rees

, et al. Risk of death from cardiovascular disease associated with low-level arsenic exposure among long-term smokers in a US population-based study. Toxicol Appl Pharmacol 2015; 287: 93–97.

Monrad

Ersbøll

Sørensen

, et al. Low-level arsenic in drinking water and risk of incident myocardial infarction: a cohort study. Environ Res 2017; 154: 318–324.

Tseng

C-H

. The potential biological mechanisms of arsenic-induced diabetes mellitus. Toxicol Appl Pharmacol 2004; 197: 67–83.

10.

Celik

Gallicchio

Boyd

, et al. Arsenic in drinking water and lung cancer: a systematic review. Environ Res 2008; 108: 48–55.

11.

Ferreccio

Yuan

Calle

, et al. Arsenic, tobacco smoke, and occupation: associations of multiple agents with lung and bladder cancer. Epidemiology 2013; 24: 898–905.

12.

Marchewka

Szymańska

Dembowski

, et al. Low molecular weight proteins and enzymes in the urine of patients with bladder cancer—a pilot study. Cent Eur J Urol 2018; 71: 280–286.

13.

Karim

Rahman

Islam

, et al. Increases in oxidized low-density lipoprotein and other inflammatory and adhesion molecules with a concomitant decrease in high-density lipoprotein in the individuals exposed to arsenic in Bangladesh. Toxicol Sci 2013; 135: 17–25.

14.

Rizwan

Naqshbandi

Farooqui

, et al. Protective effect of dietary flaxseed oil on arsenic-induced nephrotoxicity and oxidative damage in rat kidney. Food Chem Toxicol 2014; 68: 99–107.

15.

Bedir

Ozener

Emerk

. Urinary leucine aminopeptidase is a more sensitive indicator of early renal damage in non-insulin-dependent diabetics than microalbuminuria. Nephron 1996; 74: 110–113.

16.

Liew

Tay

Puthucheary

. Enzymatic and molecular characterisation of leucine aminopeptidase of Burkholderia pseudomallei. BMC Microbiol 2013; 13: 110.

17.

Tian

S-Y

Chen

S-H

Shao

B-F

, et al. Expression of leucine aminopeptidase 3 (LAP3) correlates with prognosis and malignant development of human hepatocellular carcinoma (HCC). Int J Clin Exp Pathol 2014; 7: 3752–3762.

18.

Wang

Shi

Deng

, et al. Inhibition of leucine aminopeptidase 3 suppresses invasion of ovarian cancer cells through down-regulation of fascin and MMP-2/9. Eur J Pharmacol 2015; 768: 116–122.

19.

Zhang

Yang

Shi

, et al. Overexpression of leucine aminopeptidase 3 contributes to malignant development of human esophageal squamous cell carcinoma. J Mol Histol 2014; 45: 283–292.

20.

Huang

Qiu

, et al. LAP3 promotes glioma progression by regulating proliferation, migration and invasion of glioma cells. Int J Biol Macromol 2015; 72: 1081–1089.

21.

Fang

Zhang

Yang

, et al. Leucine aminopeptidase 3 promotes migration and invasion of breast cancer cells through upregulation of fascin and matrix metalloproteinases-2/9 expression. J Cell Biochem 2019; 120: 3611–3620.

22.

Mnkandhla

Van Marwijk

Hoppe

, et al. In vivo; in vitro interaction of silver nanoparticles with leucine aminopeptidase from human and plasmodium falciparum. J Nanosci Nanotechnol 2018; 18: 865–871.

23.

Mishra

Dubey

. Inhibition of ribonuclease and protease activities in arsenic exposed rice seedlings: role of proline as enzyme protectant. J Plant Physiol 2006; 163: 927–936.

24.

Farzan

Howe

Zens

, et al. Urine arsenic and arsenic metabolites in U.S. adults and biomarkers of inflammation, oxidative stress, and endothelial dysfunction: a cross-sectional study. Environ Health Perspect 2017; 125: 127002.

25.

Kozłowska

Janasik

Nowicka

, et al. A urinary metabolomics study of a Polish subpopulation environmentally exposed to arsenic. J Trace Elem Med Biol 2019; 54: 44–54.

26.

Dutta

Saha

Mahalanobish

, et al. Melatonin attenuates arsenic induced nephropathy via the regulation of oxidative stress and inflammatory signaling cascades in mice. Food Chem Toxicol 2018; 118: 303–316.

27.

Mershiba

Dassprakash

Saraswathy

. Protective effect of naringenin on hepatic and renal dysfunction and oxidative stress in arsenic intoxicated rats. Mol Biol Rep 2013; 40: 3681–3691.

28.

Villa-Bellosta

Sorribas

. Role of rat sodium/phosphate cotransporters in the cell membrane transport of arsenate. Toxicol Appl Pharmacol 2008; 232: 125–134.

29.

Wolke

Teumer

Endlich

, et al. Serum protease activity in chronic kidney disease patients: the GANI_MED renal cohort. Exp Biol Med 2017; 242: 554–563.

30.

Sarica

Süzer

Yaman

, et al. Leucine aminopeptidase enzymuria: quantification of renal tubular damage following extracorporeal shock wave lithotripsy. Int Urol Nephrol 1996; 28: 621–626.

31.

Westhuyzen

Endre

Reece

, et al. Measurement of tubular enzymuria facilitates early detection of acute renal impairment in the intensive care unit. Nephrol Dial Transplant 2003; 18: 543–551.

32.

Quesada

Vargas

Montoro-Molina

, et al. Urinary aminopeptidase activities as early and predictive biomarkers of renal dysfunction in cisplatin-treated rats. PLoS One 2012; 7: e40402.

33.

Tsuji

Sugiura

Tsutsumi

, et al. Sex differences in the excretion levels of traditional and novel urinary biomarkers of nephrotoxicity in rats. J Toxicol Sci 2017; 42: 615–627.

34.

Janisch

Shariat

Schernhammer

, et al. The interaction of gender and smoking on bladder cancer risks. Curr Opin Urol 2019; 29: 249–255.

35.

Chen

Hsu

Chiou

, et al. Ingested arsenic, cigarette smoking, and lung cancer risk: a follow-up study in arseniasis-endemic areas in Taiwan. J Am Med Assoc 2004; 292: 2984–2990.

36.

Khairul

Wang

Jiang

, et al. Metabolism, toxicity and anticancer activities of arsenic compounds. Oncotarget 2017; 8: 23905–23926.

37.

Rackley

Yang

Pretlow

, et al. Differences in the leucine aminopeptidase activity in extracts from human prostatic carcinoma and benign prostatic hyperplasia. Cancer 1991; 68: 587–593.

38.

Huynh

Sultan

Vidovic

, et al. Retinoic acid and arsenic trioxide induce lasting differentiation and demethylation of target genes in APL cells. Sci Rep 2019; 9: 9414.

Urinary leucine aminopeptidase 3 in population environmentally exposed to airborne arsenic

Abstract

Introduction:

Aim:

Materials and Methods:

Results:

Conclusions:

Keywords

Introduction

Material and methods

Urinary arsenic

Urinary LAP3 and creatinine concentrations

Statistical analysis

Results

Multiple logistic regression model

Discussion

Conclusions

Footnotes

Acknowledgements

Data availability statement

Declaration of conflicting interests

Funding

ORCID iD

References

Urinary LAP₃ and creatinine concentrations