Environ Geochem Health DOI 10.1007/s10653-015-9691-2
ORIGINAL PAPER
Urinary stones as a novel matrix for human biomonitoring of toxic and essential elements J. Kuta • S. Smetanova´ • D. Benova´ T. Korˇistkova´ • J. Macha´t
•
Received: 30 October 2014 / Accepted: 25 February 2015 Ó Springer Science+Business Media Dordrecht 2015
Abstract Monitoring of body burden of toxic elements is usually based on analysis of concentration of particular elements in blood, urine and/or hair. Analysis of these matrices, however, predominantly reflects short- or medium-term exposure to trace elements or pollutants. In this work, urinary stones were investigated as a matrix for monitoring long-term exposure to toxic and essential elements. A total of 431 samples of urinary calculi were subjected to mineralogical and elemental analysis by infrared spectroscopy and inductively coupled plasma mass spectrometry. The effect of mineralogical composition of the stones and other parameters such as sex, age and geographical location on contents of trace and minor elements is presented. Our results demonstrate the applicability of such approach and confirm that the analysis of urinary calculi can be helpful in providing complementary information on human exposure to
Electronic supplementary material The online version of this article (doi:10.1007/s10653-015-9691-2) contains supplementary material, which is available to authorized users. J. Kuta (&) S. Smetanova´ D. Benova´ J. Macha´t Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic e-mail: [email protected] T. Korˇistkova´ Laboratory Specializing in Urinary Stones Analyses, CalculiÒ, Vra´nova 172, P.O. Box 20, 621 00 Brno, Czech Republic
trace metals and their excretion. Analysis of whewellite stones (calcium oxalate monohydrate) with content of phosphorus \0.6 % has been proved to be a promising tool for biomonitoring of trace and minor elements. Keywords Urinary stones Trace elements Biomonitoring Exposure Urolithiasis
Introduction Urinary stones are products of pathological biomineralization processes in the urinary system. About 40 components that can form urinary calculi have been identified. The most frequent components are calcium oxalates, magnesium and calcium phosphates, uric acid and their combinations (Bazin et al. 2012; Daudon et al. 2004). Urolithiasis is one of the most common health problems in the world and can affect entire population regardless of sex, age or race (Scales et al. 2012; Daudon et al. 2004). Diet and lifestyle factors can play an important role in kidney stones formation (Scales et al. 2012). Elemental composition of urinary stones is related to a particular mineral component. However, urinary stones also contain other minor or trace elements due to their natural occurrence in urine. Many researchers dealt with investigation of trace elements in urinary stones in relation to kidney stones formation (Atakan et al. 2007; Durak et al. 1992; Perk et al. 2002;
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Slojewski et al. 2010; Carpentier et al. 2011; Abboud 2008b, c); however, conclusions from such investigations are ambiguous and often contradictory (Slojewski 2011). One of the most common matrices for biomonitoring of water-soluble chemicals such as trace elements in humans is urine (Esteban and Castano 2009). Urinary stones are in permanent contact with urine, and the elements can be therefore adsorbed on or coprecipitated with the matrix of the stone. Detailed analysis of the stones can then refer to exposure to toxic elements, and urinary stones can therefore be used in biomonitoring studies. The advantage of their use lies in the fact that they reflect exposure over a longer period of time compared to blood or urine because the stones remain in the urinary tract usually months to years before the medical intervention (Burgher et al. 2004; Glowacki et al. 1992; Kang et al. 2013). Another important fact is that urinary stones can be considered as ‘‘waste’’ material in hospitals and therefore can be potentially available for analysis. As far as authors know, only a few studies were published regarding differences in contents of trace element in urinary stones related to geographical conditions (Kuta et al. 2012; Pineda-Vargas et al. 2009, 2004), smoking (Slojewski et al. 2009) or to the effect of sex and age (Kuta et al. 2012). However, use of urinary stones for biomonitoring can be limited by known mutual association of trace and minor elements with mineral constituents (Giannossi et al. 2013; Abboud 2008a; Bazin et al. 2007; Kuta et al. 2013; Slojewski et al. 2010; Wandt and Underhill 1988). These mutual associations then can act as a source of variability in the obtained results and the reason for their ambiguous interpretation. A thorough research on association of elements with urinary minerals is therefore crucial for assessment of the effect of other factors (such as age, sex, dietary habits, geography and others) on trace metal content (Kuta et al. 2013). This paper describes the results of elemental and mineralogical analysis of 431 samples of urinary stones in order to verify the applicability of urinary stones for biomonitoring of trace elements. Differences between content of trace elements in whewellite (calcium oxalate monohydrate) and uric acid stones are described. The effect of sex, age and region on trace element contents is for the first time investigated on such a large set of samples and elements.
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Experimental Samples The study was performed on 431 samples of urinary calculi (326 samples of whewellite and 105 samples of uric acid) collected during 2009–2010 from hospitals in the Czech Republic. Location of the catchment areas including number of samples per region is shown in Fig. 1. Only samples with weight over 50 mg were selected. The samples were washed in distilled water, dried at ambient temperature and homogenized in agate mortar. Samples with a known composition based on infrared spectroscopic analysis (whewellite and uric acid stones) were selected for further investigation. Available information on these samples (sex, year of birth, catchment area of hospital) was used in data processing. The age of the donors ranged between 32 and 93 years with median (as well as mean) value of 63 years. The ratio between females and males was 1:4. Analytical procedures The content of major (Ca, P and Mg) and minor elements (Na, Al, K, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Rb, Sr, Mo, Cd, Sn, Sb, Ba and Pb) was quantified by the inductively coupled plasma mass spectrometry (ICP-MS) method after sample digestion with HNO3 ? H2O2 (25 mg sample ? 2 ml of HNO3 ? 0.2 ml H2O2) in a PFA beaker on a hot plate. ICP-MS measurement (Agilent 7500ce, Agilent Technologies, Japan) was performed with a collision cell in He mode to minimize the influence of polyatomic interferences in the determination. Validation parameters of this methodology were verified by analysis of certified reference material (NIST Bone Meal) and repeated analysis of calculi samples with and without the addition of the analytes. Mineralogical composition of calculi samples was determined by FTIR spectrometry in a laboratory routinely analyzing urinary stones. Each powdered sample was mixed with potassium bromide and pressed into pellets (13 mm). A Nicolet Avatar 360 FTIR spectrometer (Thermo Scientific, USA) and the OMNIC software (Thermo Nicolet Corporation, USA) were used for analysis and interpretation of data.
Environ Geochem Health Fig. 1 Location of the catchment area (WH whewellite, UA uric acid)
Statistical analysis As a first step, robust statistics (minimum, median, maximum, 25 and 75 % percentiles) was used to describe the general concentration ranges of elements in calculi samples. Subsequently, nonparametric Mann–Whitney U test was applied to compare concentrations of elements in whewellite and uric acid stones, and Spearman’s rank correlation coefficients were calculated to study possible correlations between elements. For investigating differences in element concentrations among different groups of samples (according to sex and age of patients and catchment area of hospital), parametric three-way ANOVA was used to capture possible interactions between groups. Logarithmic transformation of data was applied to obtain normality. Prior to the ANOVA analysis, outlying values were inspected and removed (to avoid inclusion of abnormal samples). Q–Q plots and Shapiro–Wilk test were used to check normality of all tested data, and groups and homogenities of variances were tested by Bartlett’s test. Variances in age groups were inhomogeneous in case of cadmium. For this reason, Games-Howell post hoc test was used in this case. For other elements, Tukey–Kramer post hoc test was used because of unequal group sizes.
Elements containing too many values reported as below or equal to detection limit (Sn and Cr) could not fulfill normality assumption, and therefore nonparametric Kruskal–Wallis and Mann–Whitney U tests were used in these cases. ANOVA analysis was performed in R (version 3.1.0, R Core Team 2014) using ‘‘multcomp’’ package (Hothorn et al. 2008) and IBM SPSS Statistics (version 22, IBM Corp. 2013). Additional computing was performed in Statistica (version 12; StatSoft Inc. 2013) and GraphPad Prism (version 5, GraphPad Software Inc. 2007).
Results and discussion Contents of elements in whewellite and uric acid stones Selection of the stones was based on the results of analysis by infrared spectrometry, and only whewellite and uric acid stones were taken for further analysis due to known association of several elements of interest with phosphate-containing minerals (Abboud 2008a; Bazin et al. 2007; Horbarth et al. 1993; Chaudhri et al. 2007; Moroz et al. 2009; Wandt and Underhill 1988; Giannossi et al. 2013). Samples
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Environ Geochem Health
identified by IR spectrometry as ‘‘pure’’ uric acid or whewellite were subjected to ICP-MS determination of phosphorus content, and samples exceeding 0.6 % of phosphorus content were excluded from further evaluation. Variable content of phosphate minerals in studied samples set can complicate data interpretation related to assessment of the effect of other factors such as age and sex as shown in our previous study (Kuta et al. 2013). Contents of minor and trace elements were evaluated separately for uric acid and whewellite stones and can be found in Table 1. A summary of robust statistical parameters (minimum, median, maximum, 25 and 75 % percentiles) is presented. Data for Al, V, Mn, Co, Ni, Cu, As, Zr and Sb are not shown in the table due to the majority of values below or close to the limit of detection in both types of minerals. Limits of detection for these elements in mg kg-1 were as follows—3 for Al, 0.01 for V, 0.1 for Mn, 1 for Ni, 7 for Cu, 0.09 for As and Zr and 0.02 for Sb and Co. From Table 1, it can be seen that all elements have higher median contents in whewellite than in uric acid stones, with the exception of Rb and K. Regular statistical testing of differences in the contents in uric acid stones for several elements (Mg, Cr, Fe, Co, Zn, Sr, Mo, Cd, Sn, Ba and Pb) was problematic due to a high representation of values (25 % of cases and more) reported as ‘‘below detection limit’’. Mann– Whitney U test was only performed for elements whose contents in uric acid stones were above the limit of detection (P, Na, K, Se and Rb). Significant differences (p \ 0.001) were found for all tested elements except for K (p = 0.267). Similar results were found in our previous work with exception for Cr and Se where no significant difference was detected (Kuta et al. 2013, 2012). This is in agreement with work of Bazin and Giannossi (Bazin et al. 2007; Giannossi et al. 2013) who reported higher contents of metal elements in calcium oxalates (whewellite and weddellite) compared to uric acid stones. Giannossi reported higher content of Zn in uric acid and cystine stones (Giannossi et al. 2013), which is in contrast with our results and work of Bazin (Bazin et al. 2007) where higher content of Zn was found in oxalates. On the other hand, Bazin and Giannossi (Bazin et al. 2007; Giannossi et al. 2013) detected higher representation of Cu in calcium-containing stones, which is not in agreement with results of our previous study where significantly higher content of Cu was found in uric
123
acid stones compared to phosphates and oxalates (Kuta et al. 2013). The situation is different for sodium and potassium. Sodium and potassium was found in both types of urinary stones in high abundance due to naturally higher concentration of these elements in the urine. The higher molar Na/K ratio in whewellite (median of 6.3) compared to natural urinary Na/K ratio (3.6; (Hedayati et al. 2012) can correspond to exchange capabilities for Ca in the crystal lattice of oxalates due to similar ionic radius (116 pm for Na?, 114 pm for Ca2?). Lower molar Na/K ratio (median of 1.9) in the uric acid stones then suggests enrichment of potassium in a matrix of uric acid. The explanation for that may lie in the possible coexistence of ammonium urate together with uric acid during the formation of the stones (Pichette et al. 1997). The ammonium ions can be replaced by similarly sized ions of potassium or rubidium. The same mechanism was observed in the case of higher content of K and Rb in struvite (magnesium ammonium phosphate) (Kuta et al. 2013; Moroz et al. 2009). Spearman’s rank correlation coefficients for elements in whewellite can be found in Table 2. Correlation coefficients for elements in uric acid stones are not presented in the table due to the lack of data above detection limits. There are no significant correlations in whewellite stones except for weak correlation of Ba and Sr, moderate correlation of Mg and P, and Rb and K. From Table 2, no evidence of correlation of the trace elements with phosphorus content can be seen, not even for elements that can be associated with phosphate minerals (K, Rb, Na, Sr, Ba and Pb) (Kuta et al. 2013). It indicates that residual phosphorus (less that 0.6 %) in whewellite probably could not be attributed to calcium and magnesium phosphates. Consequently, the increase in the content of elements in whewellite calculi compared to uric acid calculi is not caused by higher content of phosphorus in whewellite (see Table 1) but more likely by the fact that uric acid probably does not have the ability to bind metals in the structure. Contrary, correlation of elements that are above limit of detection with phosphorus content (Na, K, Rb, Sr and Pb with correlation coefficient between 0.33 and 0.48; no significant correlation for Se) and calcium content (0.82 for Sr and 0.51 for Pb) can be found in the uric acid samples (data not presented in the table). These findings complicate the use of uric acid stones for
0.005
Detection limit
0.018
0.095
75 % percentile
Maximum
0.089
0.248
0.288
0.342
0.600
Minimum
25 % percentile
Median
75 % percentile
Maximum
Whewellite (n = 326)
0.012
Median
0.090
0.038
0.031
0.025
0.010
0.009
0.001
2420
1220
1050
940
670
1090
420
320
210
0.008 \0.001
25 % percentile
0.001
80
Na mg kg-1 50
\0.005 \0.001
0.001
Mg %
Minimum
Uric acid (n = 105)
P %
Element Unit
990
340
280
230
110
1440
370
280
230
150
K mg kg-1 60
\0.03
2.74
0.07
0.04
0.03
\0.03
273
81
65
56
39
39
5 10
\0.03
2.72
\5
\5
Fe mg kg-1 5
\0.03
\0.03
Cr mg kg-1 0.03
Table 1 Content of elements in uric acid and whewellite stones
150
50
17.6
0.7
0.5
0.4
\20 30
\0.2
1.6
0.4
0.3
0.2
\0.2
Se mg kg-1 0.2
\20
40
\20
\20
\20
\20
Zn mg kg-1 20
0.89
0.22
0.17
0.15
\0.05
1.09
0.45
0.33
0.26
0.17
Rb mg kg-1 0.05
4860
54.6
46.1
37.6
20.9
2.3
0.4
0.2
\0.2
\0.2
Sr mg kg-1 0.2
1.67
0.47
0.34
0.26
0.11
0.55
0.09
0.06
\0.05
\0.05
Mo mg kg-1 0.05
7.91
0.25
0.12
0.08
\0.02
0.42
\0.02
\0.02
\0.02
\0.02
Cd mg kg-1 0.02
32.4
1.4
0.6
0.2
\0.2
1.5
\0.2
\0.2
\0.2
\0.2
Sn mg kg-1 0.2
72.9
1.11
0.73
0.53
0.19
3.86
0.13
\0.08
\0.08
\0.08
Ba mg kg-1 0.08
68.7
4.8
3.6
2.6
0.6
2.6
0.1
0.1
\0.1
\0.1
Pb mg kg-1 0.1
Environ Geochem Health
123
0.179 1
biomonitoring because phosphorus content should be therefore counted in as a relevant factor for assessing contents of trace elements and other socio/geographical parameters. From that point of view, whewellite seems to be a more promising material for human biomonitoring of trace elements.
1
0.152
0.039
0.076
0.094
0.106
0.088
0.243
0.030
-0.024
0.015
0.318*
0.145 0.208
-0.109
0.009
0.054
0.047
0.118
0.096
-0.012 0.083
0.116 0.138
0.220
Pb Ba
Environ Geochem Health
0.116
1
1
0.052
0.038 0.042
0.074 -0.104 1
1
0.144 0.100 -0.056 0.036 1
Pb
Ba
Sn
Cd
Sr
Mo
Rb
Se
Fe
K
Cr
Na
Spearman’s rank coefficients marked as * for Rs [ 0.3, ** for Rs [ 0.6
-0.073
0.183 -0.067
-0.008 0.201
0.100 -0.025
-0.025 0.180
0.103 1
0.089 1
0.027
0.035 0.074
0.108 0.155
-0.036 0.009
-0.050 0.026
0.745** 0.054
-0.037 0.225
0.253 0.083 1
1
-0.055 0.223 -0.056 0.121 0.103 0.040 0.002 0.224 0.035 1
0.115
0.102 0.120
0.005 0.066
0.143 0.187
-0.106 0.294
0.157 -0.022
0.014 0.142
0.092 0.088
0.084 0.258
0.120 0.208
0.099 0.520*
1
1
123
Mg
P
Se Fe Cr K Na Mg P
Table 2 Spearman’s rank correlation coefficients for elements in whewellite
Rb
Sr
Mo
Cd
Sn
The effect of sex, age and region The effect of factors like sex, age and region on content of trace metals in urinary stones should be, according to previously described results, evaluated separately for uric acid and whewellite. However, regular assessment of these factors using uric acid stones is problematic due to the overall lower number of samples, higher portion of values that are below detection limits and described mineral associations. For these reasons, the effects were only assessed on whewellite stones. Descriptive statistics for all elements grouped according to age and sex can be found in Table 3, supplementary table TS1 shows statistics for regional differences. Samples from regions ‘‘P’’ and ‘‘K’’ were grouped together because of low number of the samples per region (‘‘P’’ and ‘‘K’’ are neighboring regions). Significantly higher content of Mo, Pb, Fe and Sr was found in males when compared to females, whereas Rb and Sn tend to have higher content in urinary stones of females (p \ 0.05). Male to female median ratio was found to be 1.09 for Mo, 1.19 for Pb, 1.12 for Fe, 1.06 for Sr, 0.81 for Rb and 0.71 for Sn. Increase in Cd content with increasing age of donors was revealed in both females and males. Difference between median contents of age groups 31–40 and 81–93 is 0.16 mg kg-1, which represents 3.7 fold increase in cadmium content in the oldest group of donors when compared to the youngest. However, the difference in this parameter between individual higher age categories, namely 61–70 and 71–80 (0.01 mg kg-1) and 71–80 and 81–93 (0.06 mg kg-1), is not statistically significant. Significant interactions between sex and age were found for Pb, Rb and K. Median content of Pb for males and females in the age categories covering 51–93 years oscillate around a value of 3.8 mg/kg-1. However, females in age categories 31–40 and 41–50 tend to have 2.4 times lower content of Pb compared to 51–93 years old females and males (see Fig. 2). In case of Rb, the
Environ Geochem Health Table 3 Summary statistics for contents of elements in whewellite stones related to sex and age Sex
Number of values
Age of donors
Female
Male
31–40
41–50
51–60
61–70
71–80
81–93
72
254
22
36
83
109
53
23 0.03
Cadmium (mg kg-1) Minimum
0.04
\0.2
\0.2
0.03
0.02
0.03
0.03
25 % percentile
0.08
0.08
0.05
0.06
0.07
0.09
0.08
0.12
Median
0.14
0.12
0.06
0.08
0.12
0.15
0.16
0.22
75 % percentile
0.27
0.23
0.09
0.11
0.22
0.31
0.29
0.34
Maximum
0.89
7.91
5.09
0.19
1.89
7.91
0.63
1.16
Minimum
0.15
0.11
0.15
0.17
0.17
0.12
0.11
0.19
25 % percentile
0.24
0.27
0.29
0.27
0.26
0.28
0.23
0.26
Median
0.32
0.35
0.44
0.33
0.33
0.36
0.32
0.35
Molybdenum (mg kg-1)
75 % percentile
0.41
0.49
0.52
0.46
0.46
0.47
0.48
0.50
Maximum
1.12
1.67
1.65
1.12
1.04
1.67
1.25
0.88
Minimum 25 % percentile
\0.2 0.3
\0.2 0.2
\0.2 0.3
\0.2 0.3
\0.2 0.3
\0.2 0.2
\0.2 \0.2
\0.2 0.2
Median
0.7
0.5
0.8
0.6
0.6
0.5
0.4
0.5
75 % percentile
1.8
1.2
1.4
1.4
1.4
1.2
1.5
1.2
Maximum
32.4
9.8
32.4
3.7
9.8
11.4
9.6
6.8 \0.2
Tin (mg kg-1)
Selenium (mg kg-1) Minimum
0.2
\0.2
\0.2
0.2
0.2
\0.2
0.2
25 % percentile
0.4
0.4
0.3
0.5
0.4
0.4
0.4
0.3
Median
0.5
0.5
0.5
0.6
0.6
0.5
0.5
0.5
75 % percentile
0.7
0.7
0.7
0.9
0.7
0.7
0.7
0.7
Maximum
1.7
17.6
2.0
4.7
1.6
13.6
17.6
0.9
Iron (mg kg-1) Minimum
39
40
41
41
40
41
39
25 % percentile
49
57
56
52
56
56
56
62
Median
61
68
66
62
64
66
69
68
69 143
85 273
78 143
76 135
81 190
81 221
84 273
84 162
75 % percentile Maximum
46
Chromium (mg kg-1) Minimum
\0.03
\0.03
\0.03
\0.03
\0.03
\0.03
\0.03
\0.03
25 % percentile
0.03
0.03
0.04
0.03
0.03
0.03
0.03
0.03
Median
0.04
0.05
0.04
0.04
0.05
0.05
0.05
0.03
75 % percentile
0.07
0.07
0.07
0.05
0.07
0.08
0.07
0.06
Maximum
0.14
2.74
0.14
2.74
0.31
2.33
0.47
0.14
Minimum
0.6
1.2
1.4
1.2
1.1
1.4
0.6
2.0
25 % percentile
2.1
2.8
2.4
2.0
3.1
2.5
2.9
3.0
Median
3.2
3.8
3.3
3.2
4.0
3.4
3.7
4.2
75 % percentile
4.1
4.9
4.1
4.6
5.0
4.9
4.9
5.1
Maximum
10.0
68.7
7.0
6.4
68.7
21.2
9.9
17.2
Lead (mg kg-1)
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Environ Geochem Health Table 3 continued Sex
Age of donors
Female
Male
31–40
41–50
51–60
61–70
71–80
81–93
Minimum
0.19
0.19
0.51
0.21
0.30
0.19
0.19
0.27
25 % percentile
0.48
0.54
0.63
0.49
0.57
0.51
0.54
0.53
Median
0.71
0.75
0.74
0.73
0.81
0.68
0.81
0.68
75 % percentile
1.02
1.12
1.05
1.32
1.31
1.02
1.28
0.92
Maximum
9.64
72.9
1.96
72.9
24.8
4.10
2.70
1.57
Minimum
20.9
24.3
31.2
28.7
24.4
20.9
29.3
25.1
25 % percentile
34.7
37.9
39.4
39.6
37.8
36.1
39.3
36.1
Median
43.9
46.7
44.8
44.7
46.8
44.6
46.8
43.7
75 % percentile
51.8
55.1
51.7
51.3
56.7
55.8
60.1
49.2
Maximum Rubidium (mg kg-1)
127
4860
72.9
100
127
4860.0
89.7
74.1 0.10
Barium (mg kg-1)
Strontium (mg kg-1)
Minimum
0.07
\0.05
0.11
0.03
0.09
0.05
0.07
25 % percentile
0.16
0.14
0.15
0.14
0.15
0.14
0.13
0.14
Median
0.21
0.17
0.18
0.17
0.17
0.18
0.17
0.18
75 % percentile
0.25
0.21
0.21
0.23
0.21
0.23
0.23
0.22
Maximum
0.40
0.89
0.31
0.35
0.40
0.49
0.89
0.26
Minimum
700
670
830
700
750
690
750
670
25 % percentile
920
940
910
970
940
940
930
890
Median
1030
1050
980
1060
1050
1060
1040
1020
75 % percentile
1220
1220
1220
1190
1210
1240
1230
1120
Maximum
1680
2420
1400
1710
1680
2010
2420
1620
Minimum
180
110
190
140
160
110
170
200
25 % percentile Median
240 290
230 280
230 270
230 280
220 270
230 280
230 290
250 290
Sodium (mg kg-1)
Potassium (mg kg-1)
75 % percentile
360
330
300
340
330
340
360
360
Maximum
840
990
370
420
450
840
990
490
Minimum
\20
\20
\20
\20
\20
\20
\20
\20
25 % percentile
Zinc (mg kg-1) \20
\20
20
\20
\20
\20
\20
\20
Median
30
30
40
30
30
30
30
30
75 % percentile
50
40
40
40
40
50
40
60
150
100
70
70
100
150
80
90
Maximum
highest difference between males and females was found in the 41–50 age category where median content in females was about 1.4 times higher than in males. The content of Rb is then decreasing with increasing age of females (see supplementary figure SF 1). Similar situation as for Rb can be found for K. Content of K for
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females is decreasing from the age group 41–50 up to the age group 71–80. Situation is exactly opposite in males, where content of K is continuously increasing from the 41–50 to the 81–93 age group. Females in the age category 41–50 have 1.5 times higher median content compared to males; however, the situation
Environ Geochem Health
16
-1
Pb (mg.kg )
10 6 4 3 2
3 -9 81
-8
0
0 71
-7 61
-6
0
0 51
-5 41
-4 31
-9
Males
0
3
0 81
71
-7 61
-8
0
0 -6 51
-5 41
31
-4
0
0
1
Females
Fig. 2 Difference in Pb content between sexes across the age of donors (median, quartiles, minimum and maximum values)
reverses in higher age groups, reaching a 1.2 times lower median content in females than in males in the age category of 81–93 years (see supplementary figure SF 2). Significant differences related to catchment areas and also some region–sex–age interactions were found for Rb, Cr, Fe, Zn, Se, Na and K; however, regular assessment of mentioned effects was problematic due to low number of samples in certain regions. Critical comparison of our data with previously published works dealing with contents of elements in urinary stones is problematic because data of previous studies were not presented in the way we would need for a solid evaluation (different mineralogical composition of studied sample sets, no data related to sex and age of donors). On the other hand, trends observed in our sample set can be compared to biomonitoring data from analysis of blood and urine in the same area. The National Institute of Public Health (NIPH) of the Czech Republic monitors levels of selected heavy metals and essential elements in blood and urine of Czech residents. Results from this biomonitoring program have been recently published in several papers (Bata´riova´ et al. 2006; Cˇejchanova´ et al. 2012; Cˇerna´ et al. 2012; Rambouskova´ et al. 2013, 2014; Speˇva´cˇkova´ et al. 2011). Comparison is, however, in our case, only limited to Cd, Pb, Se and Zn. Rambouskova´, Cˇerna´ and Bata´riova´ reported higher content of Pb in blood samples originating from
males compared to females (Bata´riova´ et al. 2006; Cˇerna´ et al. 2012; Rambouskova´ et al. 2014; Speˇva´cˇkova´ et al. 2011). Also, gradual increase in Pb blood concentration up to age 61 years was noted (Bata´riova´ et al. 2006; Rambouskova´ et al. 2014). This is in agreement with our results where similar trends were observed. Our results suggest that the increase in Pb content with age is predominantly caused by increase of Pb levels in females aged 31–50. Bata´riova´ reported increase in urine Cd concentration with age, which is consistent with our results (Bata´riova´ et al. 2006). Bata´riova´ also found significantly higher concentration of urinary Cd in ˇ erna´ noticed females (Bata´riova´ et al. 2006), and C that higher values of Cd in urine were previously found in females (however, not statistically significant) (Cˇerna´ et al. 2012; Benesˇ et al. 2002; Puklova´ et al. 2005). The same trend was observed in our data. Analysis of blood samples have, however, not shown any significant differences related to sex and/or age (Bata´riova´ et al. 2006; Cˇejchanova´ et al. 2012; Cˇerna´ et al. 2012; Rambouskova´ et al. 2014). As far as biogenic elements are concerned, higher content of blood Zn was found in males than females (Cˇerna´ et al. 2012; Rambouskova´ et al. 2013). We have not noticed any difference in Zn content in urinary stones related to sex; however, more than 25 % of values were lower than method detection
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limit, and proper statistical assessment was therefore ˇ erna´ and Rambouskova´ reported no not possible. C evidence of differences in blood Se concentration between males and females (Cˇerna´ et al. 2012; Rambouskova´ et al. 2013), which is in agreement with our data—we have not found any difference in content of Se in urinary calculi related to sex, either. Other elements as Mo, Sn, Cr, Fe, Rb, Ba, Sr, Na and K were not monitored in Czech population by NIPH and regular comparison of trends observed therefore could not be accomplished.
distribution can help in better understanding the processes related to sorption and coprecipitation of trace elements with matrix of urinary calculi. Acknowledgments This research was supported by the Ministry of Education of the Czech Republic (LM2011028 and LO1214) and co-funded by the European Social Fund and the state budget of the Czech Republic. We also want to thank Ondrˇej Sa´nˇka (RECETOX, Masaryk University) for creating the map for our paper.
References Conclusions Trace elements and especially toxic elements are systematically monitored in the population of many countries through the analysis of blood, urine or hair. These matrices provide data related to short-term (blood and urine) or medium-term (hair) exposure of the organism. Urinary stones are in permanent contact with urine and can remain in the urinary tract for months to years. They can therefore serve as an indicator of long-term exposure. A fact that samples can be considered as ‘‘waste’’ material in hospitals and be therefore potentially easily available for analysis can be of equal importance. Stability of the material should be also mentioned, particularly in comparison with urine or blood where some precipitation, contamination or sorption of metals may occur during storage of samples. Present work brings new results from analysis of a large set of samples of urinary stones (431 samples). The goal was to investigate whether analysis of kidney stones can be useful for biomonitoring of trace element exposure and excretion. Our results demonstrate the applicability of such an approach but also reveal importance of detailed knowledge of mineralogical composition for assessing effects of factors such as age, sex and region. We have shown that pure whewellite stones with phosphorus content below 0.6 % appear to be a promising matrix for biomonitoring. Lack of reference values for content of elements in urinary stones based on epidemiological studies with large sets of samples, however, limits the use of urinary calculi for biomonitoring at present, which implies that further research is needed to obtain such reference values. Besides, research in the fields of morphology of the stones and trace element
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Abboud, I. A. (2008a). Analyzing correlation coefficients of the concentrations of trace elements in urinary stones. Jordan Journal of Earth and Environmental Sciences, 1(2), 73–80. Abboud, I. A. (2008b). Concentration effect of trace metals in Jordanian patients of urinary calculi. Environmental Geochemistry and Health, 30(1), 11–20. Abboud, I. A. (2008c). Mineralogy and chemistry of urinary stones: Patients from north Jordan. Environmental Geochemistry and Health, 30(5), 445–463. Atakan, I. H., Kaplan, M., Seren, G., Aktoz, T., Gul, H., & Inci, O. (2007). Serum, urinary and stone zinc, iron, magnesium and copper levels in idiopathic calcium oxalate stone patients. International Urology and Nephrology, 39(2), 351–356. Bata´riova´, A., Speˇva´cˇkova´, V., Benesˇ, B., Cˇejchanova´, M., Sˇmı´d, J., & Cˇerna´, M. (2006). Blood and urine levels of Pb, Cd and Hg in the general population of the Czech Republic and proposed reference values. International Journal of Hygiene and Environmental Health, 209(4), 359–366. Bazin, D., Chevallier, P., Matzen, G., Jungers, P., & Daudon, M. (2007). Heavy elements in urinary stones. Urological Research, 35(4), 179–184. Bazin, D., Daudon, M., Combes, C., & Rey, C. (2012). Characterization and some physicochemical aspects of pathological microcalcifications. Chemical Reviews, 112(10), 5092–5120. Benesˇ, B., Speˇva´cˇkova´, V., Sˇmı´d, J., Cˇejchanova´, M., Kaplanova´, E., Cˇerna´, M., et al. (2002). Determination of normal concentration levels of Cd, Pb, Hg, Cu, Zn and Se in urine of the population in the Czech Republic. Central European Journal of Public Health, 10(1–2), 3–5. Burgher, A., Beman, M., Holtzman, J. L., & Monga, M. (2004). Progression of nephrolithiasis: Long-term outcomes with observation of asymptomatic calculi. Journal of Endourology, 18(6), 534–539. Carpentier, X., Bazin, D., Combes, C., Mazouyes, A., Rouziere, S., Albouy, P. A., et al. (2011). High Zn content of Randall’s plaque: A mu-X-ray fluorescence investigation. Journal of Trace Elements in Medicine and Biology, 25(3), 160–165. Cˇejchanova´, M., Wranova´, K., Speˇva´cˇkova´, V., Krskova´, A., Sˇmı´d, J., & Cˇerna, M. (2012). Human bio-monitoring study—toxic elements in blood of women. Central European Journal of Public Health, 20(2), 139–143.
Environ Geochem Health Cˇerna´, M., Krskova´, A., Cˇejchanova´, M., & Speˇva´cˇkova´, V. (2012). Human biomonitoring in the Czech Republic: An overview. International Journal of Hygiene and Environmental Health, 215(2), 109–119. Chaudhri, M. A., Watling, J., & Khan, F. A. (2007). Spatial distribution of major and trace elements in bladder and kidney stones. Journal of Radioanalytical and Nuclear Chemistry, 271(3), 713–720. Daudon, M., Dore, J. C., Jungers, P., & Lacour, B. (2004). Changes in stone composition according to age and gender of patients: a multivariate epidemiological approach. Urological Research, 32(3), 241–247. Durak, I., Kilic, Z., Sahin, A., & Akpoyraz, M. (1992). Analysis of calcium, iron, copper and zinc contents of nucleus and crust parts of urinary calculi. Urological Research, 20(1), 23–26. Esteban, M., & Castano, A. (2009). Non-invasive matrices in human biomonitoring: A review. [Review]. Environment International, 35(2), 438–449. Giannossi, M. L., Summa, V., & Mongelli, G. (2013). Trace element investigations in urinary stones: A preliminary pilot case in Basilicata (Southern Italy). Journal of Trace Elements in Medicine and Biology, 27(2), 91–97. Glowacki, L. S., Beecroft, M. L., Cook, R. J., Pahl, D., & Churchill, D. N. (1992). The natural history of asymptomatic urolithiasis. Journal of Urology, 147(2), 319–321. Hedayati, S. S., Minhajuddin, A. T., Ijaz, A., Moe, O. W., Elsayed, E. F., Reilly, R. F., et al. (2012). Association of urinary sodium/potassium ratio with blood pressure: Sex and racial differences. Clinical Journal of the American Society of Nephrology, 7(2), 315–322. Horbarth, K., Koeberl, C., & Hofbauer, J. (1993). Rare-earth elements in urinary calculi. Urological Research, 21(4), 261–264. Hothorn, T., Bretz, F., & Westfall, P. (2008). Simultaneous inference in general parametric models. Biometrical Journal, 50(3), 346–363. Kang, H. W., Lee, S. K., Kim, W. T., Kim, Y. J., Yun, S. J., Lee, S. C., et al. (2013). Natural history of asymptomatic renal stones and prediction of stone related events. Journal of Urology, 189(5), 1740–1746. Kuta, J., Macha´t, J., Benova´, D., Cˇervenka, R., & Korˇistkova´, T. (2012). Urinary calculi—atypical source of information on mercury in human biomonitoring. Central European Journal of Chemistry, 10(5), 1475–1483. Kuta, J., Macha´t, J., Benova´, D., Cˇervenka, R., Zeman, J., & Martinec, P. (2013). Association of minor and trace elements with mineralogical constituents of urinary stones: A hard nut to crack in existing studies of urolithiasis. Environmental Geochemistry and Health, 35(4), 511–522. Moroz, T. N., Palchik, N. A., & Dar’in, A. V. (2009). Microelemental and mineral compositions of pathogenic biomineral concrements: SRXFA, X-ray powder diffraction and vibrational spectroscopy data. Nuclear Instruments and Methods in Physics Research Section a-Accelerators Spectrometers Detectors and Associated Equipment, 603(1–2), 141–143.
Perk, H., Serel, T. A., Kosar, A., Deniz, N., & Sayin, A. (2002). Analysis of the trace element contents of inner nucleus and outer crust parts of urinary calculi. Urologia Internationalis, 68(4), 286–290. Pichette, V., Bonnardeaux, A., Cardinal, J., Houde, M., Nolin, L., Boucher, A., et al. (1997). Ammonium acid urate crystal formation in adult North American stone-formers. American Journal of Kidney Diseases, 30(2), 237–242. Pineda-Vargas, C. A., Rodgers, A. L., & Eisa, M. E. (2004). Nuclear microscopy of human kidney stones, comparison between two population groups. Radiation Physics and Chemistry, 71(3–4), 947–950. Pineda-Vargas, C. A., Eisa, M. E. M., & Rodgers, A. L. (2009). Characterization of human kidney stones using microPIXE and RBS: A comparative study between two different populations. Applied Radiation and Isotopes, 67(3), 464–469. Puklova´, V., Bata´riova´, A., Cˇerna´, M., Kotlı´k, B., Kratzer, K., Melichercˇ´ık, J., et al. (2005). Cadmium exposure pathways in the Czech urban population. Central European Journal of Public Health, 13(1), 11–19. Rambouskova´, J., Krskova´, A., Slavikova´, M., Cˇejchanova´, M., Wranova´, K., Procha´zka, B., et al. (2013). Trace elements in the blood of institutionalized elderly in the Czech Republic. Archives of Gerontology and Geriatrics, 56(2), 389–394. Rambouskova´, J., Krskova´, A., Slavı´kova´, M., Cˇejchanova´, M., & Cˇerna´, M. (2014). Blood levels of lead, cadmium, and mercury in the elderly living in institutionalized care in the Czech Republic. Experimental Gerontology, 58, 8–13. Scales, C. D., Smith, A. C., Hanley, J. M., Saigal, C. S., & Urologic Dis Amer, P. (2012). Prevalence of kidney stones in the United States. European Urology, 62(1), 160–165. Slojewski, M. (2011). Major and trace elements in lithogenesis. Central European Journal of Urology, 64(2), 58–61. Slojewski, M., Czerny, B., Safranow, K., Drozdzik, M., Pawlik, A., Jakubowska, K., et al. (2009). Does smoking have any effect on urinary stone composition and the distribution of trace elements in urine and stones? Urological Research, 37(6), 317–322. Slojewski, M., Czerny, B., Safranow, K., Jakubowska, K., Olszewska, M., Pawlik, A., et al. (2010). Microelements in stones, urine, and hair of stone formers: A new key to the puzzle of lithogenesis? Biological Trace Element Research, 137(3), 301–316. Speˇva´cˇkova´, V., Krskova´, A., Cˇejchanova´, M., Wranova´, K., Sˇmı´d, J., & Cˇerna´, M. (2011). Biological monitoring in the Czech Republic—trace elements and occupationally unexposed population. Klinicka Biochemie a Metabolismus, 19(2), 101–107. Wandt, M. A. E., & Underhill, L. G. (1988). Covariance biplot analysis of trace-element concentrations in urinary stones. British Journal of Urology, 61(6), 474–481.
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ORIGINAL PAPER
Urinary stones as a novel matrix for human biomonitoring of toxic and essential elements J. Kuta • S. Smetanova´ • D. Benova´ T. Korˇistkova´ • J. Macha´t
•
Received: 30 October 2014 / Accepted: 25 February 2015 Ó Springer Science+Business Media Dordrecht 2015
Abstract Monitoring of body burden of toxic elements is usually based on analysis of concentration of particular elements in blood, urine and/or hair. Analysis of these matrices, however, predominantly reflects short- or medium-term exposure to trace elements or pollutants. In this work, urinary stones were investigated as a matrix for monitoring long-term exposure to toxic and essential elements. A total of 431 samples of urinary calculi were subjected to mineralogical and elemental analysis by infrared spectroscopy and inductively coupled plasma mass spectrometry. The effect of mineralogical composition of the stones and other parameters such as sex, age and geographical location on contents of trace and minor elements is presented. Our results demonstrate the applicability of such approach and confirm that the analysis of urinary calculi can be helpful in providing complementary information on human exposure to
Electronic supplementary material The online version of this article (doi:10.1007/s10653-015-9691-2) contains supplementary material, which is available to authorized users. J. Kuta (&) S. Smetanova´ D. Benova´ J. Macha´t Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic e-mail: [email protected] T. Korˇistkova´ Laboratory Specializing in Urinary Stones Analyses, CalculiÒ, Vra´nova 172, P.O. Box 20, 621 00 Brno, Czech Republic
trace metals and their excretion. Analysis of whewellite stones (calcium oxalate monohydrate) with content of phosphorus \0.6 % has been proved to be a promising tool for biomonitoring of trace and minor elements. Keywords Urinary stones Trace elements Biomonitoring Exposure Urolithiasis
Introduction Urinary stones are products of pathological biomineralization processes in the urinary system. About 40 components that can form urinary calculi have been identified. The most frequent components are calcium oxalates, magnesium and calcium phosphates, uric acid and their combinations (Bazin et al. 2012; Daudon et al. 2004). Urolithiasis is one of the most common health problems in the world and can affect entire population regardless of sex, age or race (Scales et al. 2012; Daudon et al. 2004). Diet and lifestyle factors can play an important role in kidney stones formation (Scales et al. 2012). Elemental composition of urinary stones is related to a particular mineral component. However, urinary stones also contain other minor or trace elements due to their natural occurrence in urine. Many researchers dealt with investigation of trace elements in urinary stones in relation to kidney stones formation (Atakan et al. 2007; Durak et al. 1992; Perk et al. 2002;
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Slojewski et al. 2010; Carpentier et al. 2011; Abboud 2008b, c); however, conclusions from such investigations are ambiguous and often contradictory (Slojewski 2011). One of the most common matrices for biomonitoring of water-soluble chemicals such as trace elements in humans is urine (Esteban and Castano 2009). Urinary stones are in permanent contact with urine, and the elements can be therefore adsorbed on or coprecipitated with the matrix of the stone. Detailed analysis of the stones can then refer to exposure to toxic elements, and urinary stones can therefore be used in biomonitoring studies. The advantage of their use lies in the fact that they reflect exposure over a longer period of time compared to blood or urine because the stones remain in the urinary tract usually months to years before the medical intervention (Burgher et al. 2004; Glowacki et al. 1992; Kang et al. 2013). Another important fact is that urinary stones can be considered as ‘‘waste’’ material in hospitals and therefore can be potentially available for analysis. As far as authors know, only a few studies were published regarding differences in contents of trace element in urinary stones related to geographical conditions (Kuta et al. 2012; Pineda-Vargas et al. 2009, 2004), smoking (Slojewski et al. 2009) or to the effect of sex and age (Kuta et al. 2012). However, use of urinary stones for biomonitoring can be limited by known mutual association of trace and minor elements with mineral constituents (Giannossi et al. 2013; Abboud 2008a; Bazin et al. 2007; Kuta et al. 2013; Slojewski et al. 2010; Wandt and Underhill 1988). These mutual associations then can act as a source of variability in the obtained results and the reason for their ambiguous interpretation. A thorough research on association of elements with urinary minerals is therefore crucial for assessment of the effect of other factors (such as age, sex, dietary habits, geography and others) on trace metal content (Kuta et al. 2013). This paper describes the results of elemental and mineralogical analysis of 431 samples of urinary stones in order to verify the applicability of urinary stones for biomonitoring of trace elements. Differences between content of trace elements in whewellite (calcium oxalate monohydrate) and uric acid stones are described. The effect of sex, age and region on trace element contents is for the first time investigated on such a large set of samples and elements.
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Experimental Samples The study was performed on 431 samples of urinary calculi (326 samples of whewellite and 105 samples of uric acid) collected during 2009–2010 from hospitals in the Czech Republic. Location of the catchment areas including number of samples per region is shown in Fig. 1. Only samples with weight over 50 mg were selected. The samples were washed in distilled water, dried at ambient temperature and homogenized in agate mortar. Samples with a known composition based on infrared spectroscopic analysis (whewellite and uric acid stones) were selected for further investigation. Available information on these samples (sex, year of birth, catchment area of hospital) was used in data processing. The age of the donors ranged between 32 and 93 years with median (as well as mean) value of 63 years. The ratio between females and males was 1:4. Analytical procedures The content of major (Ca, P and Mg) and minor elements (Na, Al, K, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Rb, Sr, Mo, Cd, Sn, Sb, Ba and Pb) was quantified by the inductively coupled plasma mass spectrometry (ICP-MS) method after sample digestion with HNO3 ? H2O2 (25 mg sample ? 2 ml of HNO3 ? 0.2 ml H2O2) in a PFA beaker on a hot plate. ICP-MS measurement (Agilent 7500ce, Agilent Technologies, Japan) was performed with a collision cell in He mode to minimize the influence of polyatomic interferences in the determination. Validation parameters of this methodology were verified by analysis of certified reference material (NIST Bone Meal) and repeated analysis of calculi samples with and without the addition of the analytes. Mineralogical composition of calculi samples was determined by FTIR spectrometry in a laboratory routinely analyzing urinary stones. Each powdered sample was mixed with potassium bromide and pressed into pellets (13 mm). A Nicolet Avatar 360 FTIR spectrometer (Thermo Scientific, USA) and the OMNIC software (Thermo Nicolet Corporation, USA) were used for analysis and interpretation of data.
Environ Geochem Health Fig. 1 Location of the catchment area (WH whewellite, UA uric acid)
Statistical analysis As a first step, robust statistics (minimum, median, maximum, 25 and 75 % percentiles) was used to describe the general concentration ranges of elements in calculi samples. Subsequently, nonparametric Mann–Whitney U test was applied to compare concentrations of elements in whewellite and uric acid stones, and Spearman’s rank correlation coefficients were calculated to study possible correlations between elements. For investigating differences in element concentrations among different groups of samples (according to sex and age of patients and catchment area of hospital), parametric three-way ANOVA was used to capture possible interactions between groups. Logarithmic transformation of data was applied to obtain normality. Prior to the ANOVA analysis, outlying values were inspected and removed (to avoid inclusion of abnormal samples). Q–Q plots and Shapiro–Wilk test were used to check normality of all tested data, and groups and homogenities of variances were tested by Bartlett’s test. Variances in age groups were inhomogeneous in case of cadmium. For this reason, Games-Howell post hoc test was used in this case. For other elements, Tukey–Kramer post hoc test was used because of unequal group sizes.
Elements containing too many values reported as below or equal to detection limit (Sn and Cr) could not fulfill normality assumption, and therefore nonparametric Kruskal–Wallis and Mann–Whitney U tests were used in these cases. ANOVA analysis was performed in R (version 3.1.0, R Core Team 2014) using ‘‘multcomp’’ package (Hothorn et al. 2008) and IBM SPSS Statistics (version 22, IBM Corp. 2013). Additional computing was performed in Statistica (version 12; StatSoft Inc. 2013) and GraphPad Prism (version 5, GraphPad Software Inc. 2007).
Results and discussion Contents of elements in whewellite and uric acid stones Selection of the stones was based on the results of analysis by infrared spectrometry, and only whewellite and uric acid stones were taken for further analysis due to known association of several elements of interest with phosphate-containing minerals (Abboud 2008a; Bazin et al. 2007; Horbarth et al. 1993; Chaudhri et al. 2007; Moroz et al. 2009; Wandt and Underhill 1988; Giannossi et al. 2013). Samples
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identified by IR spectrometry as ‘‘pure’’ uric acid or whewellite were subjected to ICP-MS determination of phosphorus content, and samples exceeding 0.6 % of phosphorus content were excluded from further evaluation. Variable content of phosphate minerals in studied samples set can complicate data interpretation related to assessment of the effect of other factors such as age and sex as shown in our previous study (Kuta et al. 2013). Contents of minor and trace elements were evaluated separately for uric acid and whewellite stones and can be found in Table 1. A summary of robust statistical parameters (minimum, median, maximum, 25 and 75 % percentiles) is presented. Data for Al, V, Mn, Co, Ni, Cu, As, Zr and Sb are not shown in the table due to the majority of values below or close to the limit of detection in both types of minerals. Limits of detection for these elements in mg kg-1 were as follows—3 for Al, 0.01 for V, 0.1 for Mn, 1 for Ni, 7 for Cu, 0.09 for As and Zr and 0.02 for Sb and Co. From Table 1, it can be seen that all elements have higher median contents in whewellite than in uric acid stones, with the exception of Rb and K. Regular statistical testing of differences in the contents in uric acid stones for several elements (Mg, Cr, Fe, Co, Zn, Sr, Mo, Cd, Sn, Ba and Pb) was problematic due to a high representation of values (25 % of cases and more) reported as ‘‘below detection limit’’. Mann– Whitney U test was only performed for elements whose contents in uric acid stones were above the limit of detection (P, Na, K, Se and Rb). Significant differences (p \ 0.001) were found for all tested elements except for K (p = 0.267). Similar results were found in our previous work with exception for Cr and Se where no significant difference was detected (Kuta et al. 2013, 2012). This is in agreement with work of Bazin and Giannossi (Bazin et al. 2007; Giannossi et al. 2013) who reported higher contents of metal elements in calcium oxalates (whewellite and weddellite) compared to uric acid stones. Giannossi reported higher content of Zn in uric acid and cystine stones (Giannossi et al. 2013), which is in contrast with our results and work of Bazin (Bazin et al. 2007) where higher content of Zn was found in oxalates. On the other hand, Bazin and Giannossi (Bazin et al. 2007; Giannossi et al. 2013) detected higher representation of Cu in calcium-containing stones, which is not in agreement with results of our previous study where significantly higher content of Cu was found in uric
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acid stones compared to phosphates and oxalates (Kuta et al. 2013). The situation is different for sodium and potassium. Sodium and potassium was found in both types of urinary stones in high abundance due to naturally higher concentration of these elements in the urine. The higher molar Na/K ratio in whewellite (median of 6.3) compared to natural urinary Na/K ratio (3.6; (Hedayati et al. 2012) can correspond to exchange capabilities for Ca in the crystal lattice of oxalates due to similar ionic radius (116 pm for Na?, 114 pm for Ca2?). Lower molar Na/K ratio (median of 1.9) in the uric acid stones then suggests enrichment of potassium in a matrix of uric acid. The explanation for that may lie in the possible coexistence of ammonium urate together with uric acid during the formation of the stones (Pichette et al. 1997). The ammonium ions can be replaced by similarly sized ions of potassium or rubidium. The same mechanism was observed in the case of higher content of K and Rb in struvite (magnesium ammonium phosphate) (Kuta et al. 2013; Moroz et al. 2009). Spearman’s rank correlation coefficients for elements in whewellite can be found in Table 2. Correlation coefficients for elements in uric acid stones are not presented in the table due to the lack of data above detection limits. There are no significant correlations in whewellite stones except for weak correlation of Ba and Sr, moderate correlation of Mg and P, and Rb and K. From Table 2, no evidence of correlation of the trace elements with phosphorus content can be seen, not even for elements that can be associated with phosphate minerals (K, Rb, Na, Sr, Ba and Pb) (Kuta et al. 2013). It indicates that residual phosphorus (less that 0.6 %) in whewellite probably could not be attributed to calcium and magnesium phosphates. Consequently, the increase in the content of elements in whewellite calculi compared to uric acid calculi is not caused by higher content of phosphorus in whewellite (see Table 1) but more likely by the fact that uric acid probably does not have the ability to bind metals in the structure. Contrary, correlation of elements that are above limit of detection with phosphorus content (Na, K, Rb, Sr and Pb with correlation coefficient between 0.33 and 0.48; no significant correlation for Se) and calcium content (0.82 for Sr and 0.51 for Pb) can be found in the uric acid samples (data not presented in the table). These findings complicate the use of uric acid stones for
0.005
Detection limit
0.018
0.095
75 % percentile
Maximum
0.089
0.248
0.288
0.342
0.600
Minimum
25 % percentile
Median
75 % percentile
Maximum
Whewellite (n = 326)
0.012
Median
0.090
0.038
0.031
0.025
0.010
0.009
0.001
2420
1220
1050
940
670
1090
420
320
210
0.008 \0.001
25 % percentile
0.001
80
Na mg kg-1 50
\0.005 \0.001
0.001
Mg %
Minimum
Uric acid (n = 105)
P %
Element Unit
990
340
280
230
110
1440
370
280
230
150
K mg kg-1 60
\0.03
2.74
0.07
0.04
0.03
\0.03
273
81
65
56
39
39
5 10
\0.03
2.72
\5
\5
Fe mg kg-1 5
\0.03
\0.03
Cr mg kg-1 0.03
Table 1 Content of elements in uric acid and whewellite stones
150
50
17.6
0.7
0.5
0.4
\20 30
\0.2
1.6
0.4
0.3
0.2
\0.2
Se mg kg-1 0.2
\20
40
\20
\20
\20
\20
Zn mg kg-1 20
0.89
0.22
0.17
0.15
\0.05
1.09
0.45
0.33
0.26
0.17
Rb mg kg-1 0.05
4860
54.6
46.1
37.6
20.9
2.3
0.4
0.2
\0.2
\0.2
Sr mg kg-1 0.2
1.67
0.47
0.34
0.26
0.11
0.55
0.09
0.06
\0.05
\0.05
Mo mg kg-1 0.05
7.91
0.25
0.12
0.08
\0.02
0.42
\0.02
\0.02
\0.02
\0.02
Cd mg kg-1 0.02
32.4
1.4
0.6
0.2
\0.2
1.5
\0.2
\0.2
\0.2
\0.2
Sn mg kg-1 0.2
72.9
1.11
0.73
0.53
0.19
3.86
0.13
\0.08
\0.08
\0.08
Ba mg kg-1 0.08
68.7
4.8
3.6
2.6
0.6
2.6
0.1
0.1
\0.1
\0.1
Pb mg kg-1 0.1
Environ Geochem Health
123
0.179 1
biomonitoring because phosphorus content should be therefore counted in as a relevant factor for assessing contents of trace elements and other socio/geographical parameters. From that point of view, whewellite seems to be a more promising material for human biomonitoring of trace elements.
1
0.152
0.039
0.076
0.094
0.106
0.088
0.243
0.030
-0.024
0.015
0.318*
0.145 0.208
-0.109
0.009
0.054
0.047
0.118
0.096
-0.012 0.083
0.116 0.138
0.220
Pb Ba
Environ Geochem Health
0.116
1
1
0.052
0.038 0.042
0.074 -0.104 1
1
0.144 0.100 -0.056 0.036 1
Pb
Ba
Sn
Cd
Sr
Mo
Rb
Se
Fe
K
Cr
Na
Spearman’s rank coefficients marked as * for Rs [ 0.3, ** for Rs [ 0.6
-0.073
0.183 -0.067
-0.008 0.201
0.100 -0.025
-0.025 0.180
0.103 1
0.089 1
0.027
0.035 0.074
0.108 0.155
-0.036 0.009
-0.050 0.026
0.745** 0.054
-0.037 0.225
0.253 0.083 1
1
-0.055 0.223 -0.056 0.121 0.103 0.040 0.002 0.224 0.035 1
0.115
0.102 0.120
0.005 0.066
0.143 0.187
-0.106 0.294
0.157 -0.022
0.014 0.142
0.092 0.088
0.084 0.258
0.120 0.208
0.099 0.520*
1
1
123
Mg
P
Se Fe Cr K Na Mg P
Table 2 Spearman’s rank correlation coefficients for elements in whewellite
Rb
Sr
Mo
Cd
Sn
The effect of sex, age and region The effect of factors like sex, age and region on content of trace metals in urinary stones should be, according to previously described results, evaluated separately for uric acid and whewellite. However, regular assessment of these factors using uric acid stones is problematic due to the overall lower number of samples, higher portion of values that are below detection limits and described mineral associations. For these reasons, the effects were only assessed on whewellite stones. Descriptive statistics for all elements grouped according to age and sex can be found in Table 3, supplementary table TS1 shows statistics for regional differences. Samples from regions ‘‘P’’ and ‘‘K’’ were grouped together because of low number of the samples per region (‘‘P’’ and ‘‘K’’ are neighboring regions). Significantly higher content of Mo, Pb, Fe and Sr was found in males when compared to females, whereas Rb and Sn tend to have higher content in urinary stones of females (p \ 0.05). Male to female median ratio was found to be 1.09 for Mo, 1.19 for Pb, 1.12 for Fe, 1.06 for Sr, 0.81 for Rb and 0.71 for Sn. Increase in Cd content with increasing age of donors was revealed in both females and males. Difference between median contents of age groups 31–40 and 81–93 is 0.16 mg kg-1, which represents 3.7 fold increase in cadmium content in the oldest group of donors when compared to the youngest. However, the difference in this parameter between individual higher age categories, namely 61–70 and 71–80 (0.01 mg kg-1) and 71–80 and 81–93 (0.06 mg kg-1), is not statistically significant. Significant interactions between sex and age were found for Pb, Rb and K. Median content of Pb for males and females in the age categories covering 51–93 years oscillate around a value of 3.8 mg/kg-1. However, females in age categories 31–40 and 41–50 tend to have 2.4 times lower content of Pb compared to 51–93 years old females and males (see Fig. 2). In case of Rb, the
Environ Geochem Health Table 3 Summary statistics for contents of elements in whewellite stones related to sex and age Sex
Number of values
Age of donors
Female
Male
31–40
41–50
51–60
61–70
71–80
81–93
72
254
22
36
83
109
53
23 0.03
Cadmium (mg kg-1) Minimum
0.04
\0.2
\0.2
0.03
0.02
0.03
0.03
25 % percentile
0.08
0.08
0.05
0.06
0.07
0.09
0.08
0.12
Median
0.14
0.12
0.06
0.08
0.12
0.15
0.16
0.22
75 % percentile
0.27
0.23
0.09
0.11
0.22
0.31
0.29
0.34
Maximum
0.89
7.91
5.09
0.19
1.89
7.91
0.63
1.16
Minimum
0.15
0.11
0.15
0.17
0.17
0.12
0.11
0.19
25 % percentile
0.24
0.27
0.29
0.27
0.26
0.28
0.23
0.26
Median
0.32
0.35
0.44
0.33
0.33
0.36
0.32
0.35
Molybdenum (mg kg-1)
75 % percentile
0.41
0.49
0.52
0.46
0.46
0.47
0.48
0.50
Maximum
1.12
1.67
1.65
1.12
1.04
1.67
1.25
0.88
Minimum 25 % percentile
\0.2 0.3
\0.2 0.2
\0.2 0.3
\0.2 0.3
\0.2 0.3
\0.2 0.2
\0.2 \0.2
\0.2 0.2
Median
0.7
0.5
0.8
0.6
0.6
0.5
0.4
0.5
75 % percentile
1.8
1.2
1.4
1.4
1.4
1.2
1.5
1.2
Maximum
32.4
9.8
32.4
3.7
9.8
11.4
9.6
6.8 \0.2
Tin (mg kg-1)
Selenium (mg kg-1) Minimum
0.2
\0.2
\0.2
0.2
0.2
\0.2
0.2
25 % percentile
0.4
0.4
0.3
0.5
0.4
0.4
0.4
0.3
Median
0.5
0.5
0.5
0.6
0.6
0.5
0.5
0.5
75 % percentile
0.7
0.7
0.7
0.9
0.7
0.7
0.7
0.7
Maximum
1.7
17.6
2.0
4.7
1.6
13.6
17.6
0.9
Iron (mg kg-1) Minimum
39
40
41
41
40
41
39
25 % percentile
49
57
56
52
56
56
56
62
Median
61
68
66
62
64
66
69
68
69 143
85 273
78 143
76 135
81 190
81 221
84 273
84 162
75 % percentile Maximum
46
Chromium (mg kg-1) Minimum
\0.03
\0.03
\0.03
\0.03
\0.03
\0.03
\0.03
\0.03
25 % percentile
0.03
0.03
0.04
0.03
0.03
0.03
0.03
0.03
Median
0.04
0.05
0.04
0.04
0.05
0.05
0.05
0.03
75 % percentile
0.07
0.07
0.07
0.05
0.07
0.08
0.07
0.06
Maximum
0.14
2.74
0.14
2.74
0.31
2.33
0.47
0.14
Minimum
0.6
1.2
1.4
1.2
1.1
1.4
0.6
2.0
25 % percentile
2.1
2.8
2.4
2.0
3.1
2.5
2.9
3.0
Median
3.2
3.8
3.3
3.2
4.0
3.4
3.7
4.2
75 % percentile
4.1
4.9
4.1
4.6
5.0
4.9
4.9
5.1
Maximum
10.0
68.7
7.0
6.4
68.7
21.2
9.9
17.2
Lead (mg kg-1)
123
Environ Geochem Health Table 3 continued Sex
Age of donors
Female
Male
31–40
41–50
51–60
61–70
71–80
81–93
Minimum
0.19
0.19
0.51
0.21
0.30
0.19
0.19
0.27
25 % percentile
0.48
0.54
0.63
0.49
0.57
0.51
0.54
0.53
Median
0.71
0.75
0.74
0.73
0.81
0.68
0.81
0.68
75 % percentile
1.02
1.12
1.05
1.32
1.31
1.02
1.28
0.92
Maximum
9.64
72.9
1.96
72.9
24.8
4.10
2.70
1.57
Minimum
20.9
24.3
31.2
28.7
24.4
20.9
29.3
25.1
25 % percentile
34.7
37.9
39.4
39.6
37.8
36.1
39.3
36.1
Median
43.9
46.7
44.8
44.7
46.8
44.6
46.8
43.7
75 % percentile
51.8
55.1
51.7
51.3
56.7
55.8
60.1
49.2
Maximum Rubidium (mg kg-1)
127
4860
72.9
100
127
4860.0
89.7
74.1 0.10
Barium (mg kg-1)
Strontium (mg kg-1)
Minimum
0.07
\0.05
0.11
0.03
0.09
0.05
0.07
25 % percentile
0.16
0.14
0.15
0.14
0.15
0.14
0.13
0.14
Median
0.21
0.17
0.18
0.17
0.17
0.18
0.17
0.18
75 % percentile
0.25
0.21
0.21
0.23
0.21
0.23
0.23
0.22
Maximum
0.40
0.89
0.31
0.35
0.40
0.49
0.89
0.26
Minimum
700
670
830
700
750
690
750
670
25 % percentile
920
940
910
970
940
940
930
890
Median
1030
1050
980
1060
1050
1060
1040
1020
75 % percentile
1220
1220
1220
1190
1210
1240
1230
1120
Maximum
1680
2420
1400
1710
1680
2010
2420
1620
Minimum
180
110
190
140
160
110
170
200
25 % percentile Median
240 290
230 280
230 270
230 280
220 270
230 280
230 290
250 290
Sodium (mg kg-1)
Potassium (mg kg-1)
75 % percentile
360
330
300
340
330
340
360
360
Maximum
840
990
370
420
450
840
990
490
Minimum
\20
\20
\20
\20
\20
\20
\20
\20
25 % percentile
Zinc (mg kg-1) \20
\20
20
\20
\20
\20
\20
\20
Median
30
30
40
30
30
30
30
30
75 % percentile
50
40
40
40
40
50
40
60
150
100
70
70
100
150
80
90
Maximum
highest difference between males and females was found in the 41–50 age category where median content in females was about 1.4 times higher than in males. The content of Rb is then decreasing with increasing age of females (see supplementary figure SF 1). Similar situation as for Rb can be found for K. Content of K for
123
females is decreasing from the age group 41–50 up to the age group 71–80. Situation is exactly opposite in males, where content of K is continuously increasing from the 41–50 to the 81–93 age group. Females in the age category 41–50 have 1.5 times higher median content compared to males; however, the situation
Environ Geochem Health
16
-1
Pb (mg.kg )
10 6 4 3 2
3 -9 81
-8
0
0 71
-7 61
-6
0
0 51
-5 41
-4 31
-9
Males
0
3
0 81
71
-7 61
-8
0
0 -6 51
-5 41
31
-4
0
0
1
Females
Fig. 2 Difference in Pb content between sexes across the age of donors (median, quartiles, minimum and maximum values)
reverses in higher age groups, reaching a 1.2 times lower median content in females than in males in the age category of 81–93 years (see supplementary figure SF 2). Significant differences related to catchment areas and also some region–sex–age interactions were found for Rb, Cr, Fe, Zn, Se, Na and K; however, regular assessment of mentioned effects was problematic due to low number of samples in certain regions. Critical comparison of our data with previously published works dealing with contents of elements in urinary stones is problematic because data of previous studies were not presented in the way we would need for a solid evaluation (different mineralogical composition of studied sample sets, no data related to sex and age of donors). On the other hand, trends observed in our sample set can be compared to biomonitoring data from analysis of blood and urine in the same area. The National Institute of Public Health (NIPH) of the Czech Republic monitors levels of selected heavy metals and essential elements in blood and urine of Czech residents. Results from this biomonitoring program have been recently published in several papers (Bata´riova´ et al. 2006; Cˇejchanova´ et al. 2012; Cˇerna´ et al. 2012; Rambouskova´ et al. 2013, 2014; Speˇva´cˇkova´ et al. 2011). Comparison is, however, in our case, only limited to Cd, Pb, Se and Zn. Rambouskova´, Cˇerna´ and Bata´riova´ reported higher content of Pb in blood samples originating from
males compared to females (Bata´riova´ et al. 2006; Cˇerna´ et al. 2012; Rambouskova´ et al. 2014; Speˇva´cˇkova´ et al. 2011). Also, gradual increase in Pb blood concentration up to age 61 years was noted (Bata´riova´ et al. 2006; Rambouskova´ et al. 2014). This is in agreement with our results where similar trends were observed. Our results suggest that the increase in Pb content with age is predominantly caused by increase of Pb levels in females aged 31–50. Bata´riova´ reported increase in urine Cd concentration with age, which is consistent with our results (Bata´riova´ et al. 2006). Bata´riova´ also found significantly higher concentration of urinary Cd in ˇ erna´ noticed females (Bata´riova´ et al. 2006), and C that higher values of Cd in urine were previously found in females (however, not statistically significant) (Cˇerna´ et al. 2012; Benesˇ et al. 2002; Puklova´ et al. 2005). The same trend was observed in our data. Analysis of blood samples have, however, not shown any significant differences related to sex and/or age (Bata´riova´ et al. 2006; Cˇejchanova´ et al. 2012; Cˇerna´ et al. 2012; Rambouskova´ et al. 2014). As far as biogenic elements are concerned, higher content of blood Zn was found in males than females (Cˇerna´ et al. 2012; Rambouskova´ et al. 2013). We have not noticed any difference in Zn content in urinary stones related to sex; however, more than 25 % of values were lower than method detection
123
Environ Geochem Health
limit, and proper statistical assessment was therefore ˇ erna´ and Rambouskova´ reported no not possible. C evidence of differences in blood Se concentration between males and females (Cˇerna´ et al. 2012; Rambouskova´ et al. 2013), which is in agreement with our data—we have not found any difference in content of Se in urinary calculi related to sex, either. Other elements as Mo, Sn, Cr, Fe, Rb, Ba, Sr, Na and K were not monitored in Czech population by NIPH and regular comparison of trends observed therefore could not be accomplished.
distribution can help in better understanding the processes related to sorption and coprecipitation of trace elements with matrix of urinary calculi. Acknowledgments This research was supported by the Ministry of Education of the Czech Republic (LM2011028 and LO1214) and co-funded by the European Social Fund and the state budget of the Czech Republic. We also want to thank Ondrˇej Sa´nˇka (RECETOX, Masaryk University) for creating the map for our paper.
References Conclusions Trace elements and especially toxic elements are systematically monitored in the population of many countries through the analysis of blood, urine or hair. These matrices provide data related to short-term (blood and urine) or medium-term (hair) exposure of the organism. Urinary stones are in permanent contact with urine and can remain in the urinary tract for months to years. They can therefore serve as an indicator of long-term exposure. A fact that samples can be considered as ‘‘waste’’ material in hospitals and be therefore potentially easily available for analysis can be of equal importance. Stability of the material should be also mentioned, particularly in comparison with urine or blood where some precipitation, contamination or sorption of metals may occur during storage of samples. Present work brings new results from analysis of a large set of samples of urinary stones (431 samples). The goal was to investigate whether analysis of kidney stones can be useful for biomonitoring of trace element exposure and excretion. Our results demonstrate the applicability of such an approach but also reveal importance of detailed knowledge of mineralogical composition for assessing effects of factors such as age, sex and region. We have shown that pure whewellite stones with phosphorus content below 0.6 % appear to be a promising matrix for biomonitoring. Lack of reference values for content of elements in urinary stones based on epidemiological studies with large sets of samples, however, limits the use of urinary calculi for biomonitoring at present, which implies that further research is needed to obtain such reference values. Besides, research in the fields of morphology of the stones and trace element
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