Reference intervals of 24 trace elements in blood, plasma and erythrocytes for the Slovenian adult population

Study population

Study subjects (n=192; 107 women and 85 men) were blood donors (84.9 % from Central Slovenia, within 30 km from Ljubljana) who were included in the study on a voluntary basis by the Blood Transfusion Centre of Slovenia (BTC) between September and December 2014 through a priori selection. Non-fasting morning venous blood was collected from the participants, who had, following the BTC protocol, doctor’s consent to be eligible for blood donation. Of the participants, 59.9 % were from urban environments (population size >2,500) and 40.1 % were from rural environments (population size <2,500). According to the national environmental data on selected TEs collected and evaluated in a study of Snoj-Tratnik et al. [5], none of the study’s participants was from an historically metal(loid)-contaminated environment. Inclusion criteria for participants were that must be aged between 18 and 65 years and be in a healthy condition. Participants were equally included in four subgroups created according to participant age to ensure even distribution over the entire age frame: 18–29 years; (19 women, 22 men), 30–39 years (23 women, 22 men), 40–49 years (36 women, 19 men) and 50–65 years (28 women, 22 men). All participants signed their written consent and filled out the questionnaire with information about their age, gender, living environment, eating habits (seafood intake, vegetarian/mixed diet, local/imported food consumption), smoking habits, and whether they took food supplements or/and medications. Thirty-seven (19.3 %) participants were on medication, mostly for cardiovascular, thyroid diseases and/or analgetics, and three were taking oestrogen hormones; however, their status was under control, and they were eligible for blood donation. Lipemia and haemolysis were exclusion criteria. Only one participant reported possible occupational exposure (as a dentist). No questions on social status and body mass index were included in the questionnaire. The National Medical Ethics Committee (KME 83/04/08 and 109/02/13) approved the study.

Samples

Well-trained and experienced phlebotomists collected 192 blood samples in 6 mL K₂EDTA BD Vacutainer^® tubes for TEs. Tubes were tested for TEs content according to the laboratory’s own protocol and CLSI recommendations [6].

Blood samples were divided into two aliquots. One of the aliquots was centrifuged at 2,000×g for 10 min to obtain plasma and erythrocytes within 2 h after blood collection. Erythrocytes were washed three times with saline solution and the erythrocytes’ haematocrit in washed packed cells was measured [7]. Blood haematocrit was not obtained. All blood, plasma and washed erythrocyte samples were stored at −20 °C until analysis.

Determination of TEs in blood, plasma and erythrocyte samples

TEs (Mn, Co, Cu, Zn, Se, Mo, Li, Be, V, Cr, Ni, Ga, As, Rb, Sr, Ag, Cd, Sn, Cs, Au, Hg, Tl, Pb and U) were determined in blood, plasma and erythrocytes at the Institute of Clinical Chemistry and Biochemistry at the University Medical Centre, Ljubljana. All samples were thawed and brought to room temperature before analysis. Measurements of prepared samples, calibrators and control samples were made on an ICP-MS with Octopole Reaction System (7700x, Agilent Technologies, Japan) as previously described, with minor changes in standard concentration solutions [8]. An aliquot of every blood, plasma, washed erythrocyte sample, calibrator or control sample was mixed with an ammonium hydroxide solution containing Triton X-100, 1-butanol, ethylenediaminetetraacetic acid disodium salt dehydrate and an internal standard solution containing Bi, Ge, In, 6Li, Lu, Rh, Sc and Tb. The reagents were TEs grade. Fourteen points calibration for blood and plasma and 18 points calibration for erythrocyte samples were performed. The reference material (RM) Seronorm Trace Elements Whole Blood L-1 and L-2 and Serum L-1 (Sero) were used to check the accuracy of the results.

Erythrocyte TEs values in every sample were normalised by washed erythrocytes’ haematocrit to overcome methodological errors.

Limits of blank (LoB), limits of detection (LoD) and limits of quantification (LoQ) for all trace elements for our method were determined according to CLSI recommendations, with a classical approach [9] using RM Seronorm Trace Elements Urine L-1 and L-2 (Sero) in different dilutions to obtain minimally positive samples.

RMs were analysed according to the protocol for internal quality control at the beginning and at the end of the run and between runs on every 15–20 samples. The values found were in good agreement with the manufacturer–assigned RM values. Our laboratory has also successfully participated in the INSTAND External Quality Assessment Scheme with validated ICP-MS methods for over 8 years.

Statistics

Statistical analysis was performed as recommended by IFCC/CLSI guidelines [3, 4] using IBM SPSS Statistics 27.0.1.0 (IBM Corporation) and MedCalc 11.4.2.0 (MedCalc Software Ltd). For statistical calculations, the LoD/2 for values below LoD were assigned. For each TE, distribution was assessed using the Kolmogorov–Smirnov test. Outliers were excluded using Tukey’s method [10] but only after visual inspection. Gender differences were analysed by t-test for independent samples or by Mann-Whitney U test. An Independent-Samples Kruskal Wallis test and a one-way ANOVA test with Bonferroni correction for multiple tests for differences between age subgroups were used. A Spearman’s rank-order correlation was run to determine the relationship between blood, plasma and erythrocyte TEs levels and age, seafood consumption, smoking status, number of cigarettes smoked per day or number of amalgam fillings.

Descriptive statistics

Our group consisted of 192 individuals, 107 women (55.7 %) and 85 men (44.3 %), with no significant differences in the number of participants between gender groups (χ² (1)=2.521, p=0.112) and no age differences between genders (p=0.239) (Table 1).

Four age subgroups were equal in terms of the number of participants (p=0.453) and gender, except for the subgroup of age 40–49 years, where the number of women was significantly higher (p=0.016) (see Supplementary Material, Figure S1).

According to self-reported data, there were 125 (65.1 %) non-smokers, 22 (11.5 %) ex-smokers, 14 (7.3 %) passive-smokers and 29 (15.1 %) smokers, with mean cigarette consumption of 10.68 (SD=6.2, min=2, max=20) cigarettes per day and no significant difference between genders (p=0.175). In the smoker group, there were 19 light smokers, 10 moderate smokers and no heavy smokers (≤10; 11–24; ≥25 cigarettes per day) (see Supplementary Material, Figure S2).

Participants consumed seafood up to 3.5 times a week, with a median value for both genders of 1.0 (IQR 1.0–1.0) and with the majority consumption once per week (70.1 % women and 63.5 % men) (see Supplementary Material, Figure S3).

On average, our group had 3.69 (n=148, SD=3.7, min=1, max=17) amalgam fillings, with no significant difference between genders (p=0.713). In regard to amalgam fillings, 22.9 % of participants had none, 37.5 % had 1–5, 25.0 % had 5–10, and a minority (4.1 %) had above 10 amalgam fillings. For the rest of the participants, the data was missing (see Supplementary Material, Figure S4).

Establishing the essential and non-essential trace elements RIs

For all essential TEs, we set lower reference limits (LRL) at the 2.5th percentile and upper reference limits (URL) at the 97.5th percentile according to CLSI recommendations after outlier exclusion was set [3]. Calculated LRL and URL values with their 90 % confidential intervals (CIs), medians and Interquartile Ranges (IQRs) along percentage of samples with values under LoD are presented in Table 2. For all non-essential TEs, only URL at the 97.5th percentile was defined, and calculated URL values with their 90 % CI, medians, and IQRs with the percentage of samples with values under LoD can be found in Table 3.

All TE values were also verified according to available common influencing factors (gender, age, smoking, seafood consumption and the presence of amalgam fillings) to evaluate their possible impact.

Smoking, seafood and amalgam fillings

As expected, we found a statistically significant positive correlation between blood (p<0.001) and erythrocyte (p<0.001) Cd with smoking status and blood (p=0.036) and erythrocyte (p=0.044) Cd with the number of smoked cigarettes per day. Significant differences in blood (p<0.001) and erythrocyte (p<0.001) Cd in subgroups according to smoking status were also seen (Figure 1A, B).

Figure 1:

Blood (A) and erythrocyte (B) Cd distribution according to smoking status. Boxes represent the median, 25th and 75th percentile, whiskers mark the minimum and maximum values excluding outliers. Dots represent potential outliers and high extreme values are labelled with an asterisk.

Arsenic, mercury, zinc and selenium levels were affected by and positively correlated with seafood consumption (Table 4). Positive correlations between the number of amalgam fillings and Hg, Ag and Cu were found (Table 4).

Establishing RIs and values under LoD

For essential TEs in blood, plasma and erythrocytes RIs were determined with LRL (set near the 2.5th percentile) and URL (set near the 97.5th percentile). If the value at the 2.5th percentile was under LoD, as in the case of blood Co and Mo and plasma Mn, only a URL near the 97.5th percentile was proposed. For non-essential TEs, only the URL near the 97.5th percentile was placed. Although, the ICP-MS methodology, due to high sensitivity and low LoDs, enabled us to measure elements of very low levels, in some cases, the majority of values were under LoD, mostly from a group of non-essential TEs [Table 3], and only a few were from the group of essential TEs, namely blood Co, plasma Mn, erythrocyte Co and erythrocyte Mo (Table 2). Considering the Environmental Protection Agency guidelines for analysing data with values below LoDs [11, 12] we suggest that RIs with over 15 % of values under LoD should be considered with caution.

Data comparison

As Nisse et al. stated [13], regardless of similarities in TEs levels found between different published data, it is difficult to compare results between different studies, because of environmental exposure and intrinsic population differences. The complexity of comparison is attributed to differences in the studied population sampling protocols and analytical methods, data and results processing and outlier detection methods [13], [14], [15], which can result in differences in RIs between studies [16]. Also, published data overview from several authors [5, 13, 14, 16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28] reveals a variety of approaches in presented data: from different percentiles to means, medians, setting limits on different percentiles, censoring data and differences in selected populations. Nevertheless, we performed a vague comparison of our data with published levels to get at least a rough estimation of similarities or differences.

Comparisons of our established RIs in the general Slovenian population with RIs for other world populations [5, 13, 14, 16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29] show that we are in the European average, which is to be expected, as Slovenia is geologically, industrially and in terms of food consumption similar to other European countries (see Supplementary Material, Tables S3 and S4). Similarities are expected, as this is a general adult population with no extremes in potential physical activity, chronic diseases and occupational or environmental exposure [18, 22, 29]. Still, for some TEs our values fall outside the average, confirming the importance of using laboratory- and population-specific values when evaluating disease states and the status of TEs in the body, as sometimes minimal differences can play an important role in diagnosis.

TEs in erythrocytes

Although plasma and blood are the most used samples for assessing the status of essential and non-essential TEs, there are advantages in assessing their levels in erythrocytes. Erythrocyte TEs concentrations are useful for assessing TEs intracellular concentrations and their general homeostasis and long-term exposure and in certain pathological conditions such as inflammatory response or anaemia [32, 33]. For instance, red blood cell (RBC) concentrates are the major blood component transfused worldwide to treat severe anaemia [34].

However, the published data on various TEs erythrocyte levels is rare [17, 35]. Heitland and Köster’s [17] TEs levels in erythrocytes have been determined indirectly by calculation, using blood and plasma concentrations and blood haematocrit. However, we found the determination of TEs directly from washed erythrocytes better and more reliable for clinical purposes, so we measured an extended number of TE levels in washed erythrocytes normalised by washed erythrocyte haematocrits. Essential TE levels in the erythrocytes in the non-exposed northern German population [17] were comparable with our population for Mn, Co, Se and Mo, while our levels of Zn and Cu were lower (see Supplementary Material, Table S5).

Gender and age

Gender-specific LRLs and/or URLs were established for most essential TEs in blood, plasma and erythrocytes [Table 2]. Our blood and plasma Zn levels, but not erythrocyte Zn levels, were gender- and age-dependent and this agrees with other authors [36], [37], [38], [39].

We found significantly lower blood Zn levels in age subgroup 30–39 years in both genders (Figure 2A, B). The lower Zn levels in the group under 40 years were also described by some other authors [20, 29]. In men, there was also a negative trend in plasma Mo levels with age (Figure 2C, D). Women had higher blood and erythrocyte Mn, and this is in accordance with several other authors [13, 14, 18, 19]. Consistent with other studies [31, 40], we also found that women had significantly higher plasma Cu levels and significantly lower plasma Zn and Se levels than men (see Supplementary Material, Figure S5). Women also had significantly lower plasma Mn and Zn, blood Zn, and erythrocyte Cu levels. The differences can be attributed to gender-specific physiology and its changes occurred within a broad age range of the subjects included in our study. In our population, women had lower blood and erythrocyte Pb levels, and a positive trend according to age in both genders was seen (Figure 3A, B). This data is also supported by some other authors [13, 14, 19, 31, 41], which is expected, as the skeleton acts as a storage depot for absorbed Pb, and approximately 40–70 % of blood Pb can come from the skeleton in environmentally exposed adults [42], and this fraction can be on the higher end, particularly during lactation, menopause, osteoporosis and old age [43, 44]. Blood and plasma Sr levels in women and men, increase with age (Figure 3C, D). It is known that absorbed Sr is primarily distributed to the bone [45, 46]. So presumably, in conditions with larger bone turnover, Sr blood levels would also be higher [47]. However, to confirm age- and gender-related differences and determine age-specific RIs, further investigations on more data (and multiple regression modelling) are needed.

Figure 2:

Blood Zn (A, B) and plasma Mo (C, D) distribution according to age subgroup and gender. Boxes represent the median, 25th and 75th percentile, whiskers mark the minimum and maximum values excluding outliers. Dots represent potential outliers and high extreme values are labelled with an asterisk.

Figure 3:

Blood (A) and erythrocyte (B) Pb, blood (C) and plasma (D) Sr distribution according to age and gender. Boxes represent the median, 25th and 75th percentile, whiskers mark the minimum and maximum values excluding outliers. Dots represent potential outliers and high extreme values are labelled with an asterisk.

Smoking, seafood consumption and amalgam fillings

As expected, and in accordance with other authors [13, 14, 24, 30, 31, 48], significantly higher Cd blood and erythrocyte levels in smokers compared to non-smokers were found. And, in line with previously published papers [13, 27], a significant positive correlation of blood Cd and erythrocyte Cd, Pb, Cs, and Rb with the number of smoked cigarettes per day and negative correlation for blood and erythrocyte Se was found. As expected [24, 49, 50], our population blood As, Hg, Zn and Se levels were positively affected by seafood consumption and were higher in those consuming seafood more than once per week. Also, levels in erythrocytes and plasma were higher, except for plasma Hg.

A number of amalgam fillings had positive correlations with blood and plasma Hg, Ag and Cu. This association was previously described [51, 52]; moreover, their levels in plasma and erythrocytes decreased after amalgam removal [53].

Strengths and limitations

Establishing RIs for an extended number of TEs, particularly non-essential ones, and simultaneous measurement of TEs in whole blood, plasma and erythrocytes from the same sample of each participant and with equal participants’ distribution over a wide age range is one of the main strengths of our study. RIs for TEs established in our study are the first for the Slovene adult general population; loose inclusion criteria enabled us to get a wider and, in some respects, more reliable insight.

Although the small number of participants is within the range of sufficient numbers, it represents a weakness of our study, because the results obtained on a larger sample set would be more robust.

Moreover, for some elements (such as blood and erythrocyte Co), we hit a limit with our method. As we are aware of the possible contamination pathways and follow specific protocols to prevent contamination, another analytical and sample preparation technique would likely have to be used to evaluate these TEs.