Journal of Trace Elements in Medicine and Biology 28 (2014) 448–452
Contents lists available at ScienceDirect
Journal of Trace Elements in Medicine and Biology journal homepage: www.elsevier.de/jtemb
ISTERH Conference Proceedings
Zinc transporter gene expression and glycemic control in post-menopausal women with Type 2 diabetes mellitus Meika Foster a , Anna Chu a , Peter Petocz b , Samir Samman a,∗ a b
Discipline of Nutrition & Metabolism, School of Molecular Bioscience, University of Sydney, NSW 2006, Australia Department of Statistics, Macquarie University, NSW 2109, Australia
a r t i c l e
i n f o
Keywords: Glucose Insulin Zinc transporter Gene expression Type 2 diabetes mellitus
a b s t r a c t Type 2 diabetes mellitus (DM) is associated often with underlying zinc deficiency and nutritional supplements such as zinc may be of therapeutic benefit in the disease. In a randomized, double-blind, placebo-controlled, 12-week trial in postmenopausal women (n = 48) with Type 2 DM we investigated the effects of supplementation with zinc (40 mg/d) and flaxseed oil (FSO; 2 g/d) on the gene expression of zinc transporters (ZnT1, ZnT5, ZnT6, ZnT7, ZnT8, Zip1, Zip3, Zip7, and Zip10) and metallothionein (MT-1A, and MT-2A), and markers of glycemic control (glucose, insulin, glycosylated hemoglobin [HbA1c]). The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated. No significant effects of zinc or FSO supplementation were observed on glycemic marker concentrations, HOMA-IR or fold change over 12 weeks in zinc transporter and metallothionein gene expression. In multivariate analysis, the change over 12 weeks in serum glucose concentrations (P = 0.001) and HOMA-IR (P = 0.001) predicted the fold change in Zip10. In secondary analysis, marginal statistical significance was observed with the change in both serum glucose concentrations (P = 0.003) and HOMA-IR (P = 0.007) being predictive of the fold change in ZnT6. ZnT8 mRNA expression was variable; HbA1c levels were higher (P = 0.006) in participants who exhibited ZnT8 expression compared to those who did not. The significant predictive relationships between Zip10, ZnT6, serum glucose and HOMA-IR are preliminary, as is the relationship between HbA1c and ZnT8; nevertheless the observations support an association between Type 2 DM and zinc homeostasis that requires further exploration. © 2014 Elsevier GmbH. All rights reserved.
Introduction Zinc dyshomeostasis and increased levels of oxidative stress play major roles in the pathogenesis of Type 2 diabetes mellitus (DM) [1]. Zinc is known to elicit insulin-like effects and it is this property that is most likely affected by the alterations in zinc distribution and metabolism associated with DM. Zinc deficiency associated with DM may impair the ability of zinc to induce the expression of zinc binding proteins, namely metallothionein (MT), and thereby increase the risk of oxidative stress-induced damage. Other critical pathways that are affected in DM and which are influenced by zinc include those of lipid metabolism, inflammation and insulin signalling [1]. Under normal conditions zinc is found throughout the pancreas, where it forms an integral component of the insulin crystalline structure [2], serving to stabilize the
∗ Corresponding author at: Department of Human Nutrition, University of Otago, PO Box 56, Dunedin 9054, New Zealand. E-mail address: [email protected] (S. Samman). http://dx.doi.org/10.1016/j.jtemb.2014.07.012 0946-672X/© 2014 Elsevier GmbH. All rights reserved.
insulin granule by rendering it less soluble [3]. Zinc transporter 8 (ZnT8) is responsible for delivering zinc ions from the cytoplasm of pancreatic -cells to insulin granules, which are subsequently secreted as a zinc-rich complex. Recent evidence suggests that single nucleotide polymorphisms in the ZnT8 gene are associated with impaired proinsulin conversion [4] and an increased risk of developing Type 2 DM [5]. Perturbed zinc homeostasis in DM appears to lead to a state of conditioned (secondary) zinc deficiency, evidenced in part by hyperzincuria that is reported to be present in the disease, and therefore zinc replenishment may exert a favourable effect. In a meta-analysis of randomised controlled trials that was conducted to determine the effect of zinc on markers of glycemic control, we reported a reduction in fasting serum glucose concentrations and a tendency for glycosylated hemoglobin (HbA1c) to decrease after zinc supplementation [6]. The interaction between glycemic markers and the gene expression of zinc transporters in humans is unclear. The aim of the present study is to examine the relationships between markers of glycemic control and the gene expression of MT and specific zinc transporters in women with Type 2 DM.
M. Foster et al. / Journal of Trace Elements in Medicine and Biology 28 (2014) 448–452
Zinc transporters were selected to canvass import and export functions across both the plasma and intracellular vesicular membranes and/or because they had been shown to be zinc-responsive in previous studies in humans, animal models and cell culture systems [7]. Methods and materials The trial design and participant details have been reported previously in papers exploring the effects of zinc and flaxseed oil (FSO) supplementation on markers of lipidemia and glycemia [8] and the relationships between zinc transporter and MT gene expression and inflammation [9]. In the present study we undertook a secondary analysis to determine the relationship between markers of glycemia and the gene expression of zinc transporters. Briefly, women were enrolled in the trial if they were post-menopausal (no menses for >12 mo) with Type 2 DM, and had a glomerular filtration rate and micro-albumin/creatinine ratio in the normal range. Exclusion criteria were: the use of insulin; smoking; and diagnosis with any current major illness other than DM. The Human Research Ethics Committee of the University of Sydney approved the study protocol and all participants provided written informed consent. The protocol was registered at http://www.ClinicalTrials.gov, with the identifier NCT01505803. The study was a randomized, double-blind, placebo-controlled trial conducted over 12 weeks. Upon enrolment, 48 participants were randomized into four equal groups to receive 40 mg/d elemental zinc, 2 g/d FSO, both zinc and FSO, or placebo. Venous blood samples were collected at 4-weekly intervals from participants after an overnight fast of at least 10 h. Cell preparation tubes (CPT vacutainers; Becton Dickinson) were used for the isolation of peripheral blood mononuclear cells (PBMC), serum gel tubes for glucose and insulin analyses, EDTA tubes for analysis of HbA1c, and trace metal tubes (Becton Dickinson) for plasma zinc analysis. Insulin resistance was estimated using the homeostasis model assessment (HOMA-IR) calculation [10].
449
Table 1 Biomarkers of glycemic control at baseline and week 12 in participants who were supplemented with zinc (n = 23) or not supplemented with zinc (n = 20).
Glucose (mmol/L) All Zn Control HbA1c (%) All Zn Control Insulin (pmol/L) All Zn Control HOMA-IR All Zn Control
Baseline
Week 12
Change
6.94 ± 0.26 6.77 ± 0.17 7.15 ± 0.53
6.87 ± 0.25 7.00 ± 0.66
0.11 ± 0.17 −0.16 ± 0.22
6.68 ± 0.15 6.55 ± 0.09 6.83 ± 0.30
6.73 ± 0.12 6.83 ± 0.32
0.18 ± 0.09 −0.01 ± 0.07
68.5 ± 5.51 63.0 ± 8.18 74.8 ± 7.18
69.8 ± 10.20 68.9 ± 4.95
3.52 ± 0.32 3.17 ± 0.43 3.93 ± 0.47
3.54 ± 0.49 3.53 ± 0.37
6.78 ± 5.32 −5.9 ± 5.22
0.36 ± 0.28 −0.40 ± 0.33
Data expressed as mean ± SE. HbA1c, glycosylated haemoglobin; HOMA-IR, homeostasis model of assessment–insulin resistance. Reference ranges for outcome measures are: glucose, 3.0–7.7 mmol/L; insulin, 10–96 pmol/L; HbA1c, 3.5–6.0%.
mRNA and participants in whom ZnT8 mRNA was not expressed were conducted using unpaired student t-tests. Principal component analysis was used to identify “clusters” of zinc transporter and MT gene expression, and multivariate and univariate ANOVA models were used to determine whether the glycemic markers (serum glucose, serum insulin, HOMA-IR, HbA1c) predicted any of the specific zinc transporter or MT mRNA or any of the identified clusters. Statistical analyses were carried out using SPSS v18. P < 0.01 was interpreted as statistically significant, with the exception that a conservative value of P < 0.001 was adopted for multivariate and univariate analyses due to the large number of test results under investigation. Results
Zinc transporter and metallothionein gene expression The method for measuring zinc transporter and MT mRNA expression has been described previously [9,11]. In brief, PBMC from individual samples were extracted and total RNA was prepared (Applied Biosystems-Life Technologies Australia Pty Ltd, Victoria, Australia) and reverse transcribed into cDNA (InvitrogenLife Technologies Australia Pty Ltd, Victoria, Australia) using commercially available kits. RNA integrity was assessed. Purity and yield of the isolated RNA were determined by UV spectrophotometry, with all samples generating an A260:A280 ratio within the range of 1.8–2.1. RNA integrity was verified by ethidium bromide staining after 1% denaturing agarose gel electrophoresis. Relative quantification of zinc transporter mRNA (ZnT1, ZnT5, ZnT6, ZnT7, ZnT8, Zip1, Zip3, Zip7, and Zip10), and MT (MT-1A, and MT-2A) was conducted using Taqman real-time PCR (ABI 7500 Fast Sequence Detection System; Applied Biosystems-Life Technologies Australia Pty Ltd, Victoria, Australia). Expression levels were normalized to 18S rRNA and quantified using the CP method, and fold change was quantified using the CP method. Statistical analysis Differences in the concentrations of biochemical measures over time within each treatment group were assessed using multivariate analysis. Post-hoc investigations using student t-tests were undertaken to compare the results of all participants who received zinc supplements with all participants who were not supplemented with zinc. Comparisons between participants who expressed ZnT8
Forty-three participants completed the trial and were included in the statistical analysis. The mean age and BMI were, respectively, 65.0 ± 7.8 y (mean ± SD) and 28.6 ± 5.1 kg/m2 . The plasma zinc concentration of participants at baseline was 12.8 ± 0.3 mol/L (mean ± SE) and within the reference range (10–18 mol/L). Serum concentrations of the glycemic measures were within their respective reference intervals, except for HbA1c, which was above the normal range (Table 1). Significant increases in plasma zinc were observed over time in the groups supplemented with zinc and both zinc and FSO (P = 0.002 and P = 0.019, respectively), but not in the groups supplemented with FSO alone or placebo. There were no statistically significant effects of zinc supplementation on HbA1c, serum glucose and insulin concentrations, or HOMA-IR when analysed by treatment group [8]; nor when grouped according to whether participants received (n = 23) or did not receive (n = 20) zinc as part of their intervention (Table 1). There were no significant differences in the baseline expression of any of the zinc transporter or MT mRNA in participants who received zinc compared to those who did not receive zinc as part of their intervention [9]. ZnT8 mRNA expression was detected only in 21 participants; compared to participants in whom ZnT8 mRNA was not expressed, participants who expressed ZnT8 mRNA were observed to have higher HbA1c levels (6.75% vs. 6.31%; P = 0.006). There were no significant differences between baseline and week 12 zinc transporter (including ZnT6 and Zip10; Fig. 1), and MT mRNA expression in participants, irrespective of zinc
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M. Foster et al. / Journal of Trace Elements in Medicine and Biology 28 (2014) 448–452
Fig. 1. Relative mRNA expression of ZnT6 (Panel A) and Zip10 (Panel B) at baseline and week 12 in participants who were supplemented with zinc (n = 23) or not supplemented with zinc (n = 20). In multivariate analysis, the change in serum glucose concentrations and HOMA-IR predicted the fold change in Zip10. In secondary analysis statistical significance was observed with the change in both serum glucose concentrations and HOMA-IR being predictive of the fold change in ZnT6 and Zip10 (see details in Table 2). Values are shown as mRNA per 106 18S rRNA, and expressed as mean ± SE.
supplementation. No significant up- or down-regulation of gene expression in response to zinc supplementation was observed. In univariate analysis, the change in both serum glucose concentrations (P = 0.001) and HOMA-IR (P = 0.001) predicted the fold change in Zip10 (Table 2). Principal component analysis of expression levels at baseline revealed 3 clusters, each containing zinc transporter or MT mRNA, that behaved in a similar manner. The clusters were identified as cluster 1: ZnT5, ZnT7, Zip1, Zip7
and Zip10; cluster 2: ZnT1, ZnT6, ZnT8 and Zip3; and cluster 3: MT-1A and MT-2A. A multivariate ANOVA model was used to determine the relationships between glycemic markers and mRNA expression within the clusters. No significant relationships were observed by multivariate ANOVA, however univariate analysis of cluster 2 revealed marginal statistical significance with the change in both serum glucose (P = 0.003) and HOMA-IR (P = 0.007) being predictive of the fold change in ZnT6 (Table 2).
Table 2 Multivariate analysis of variance models using change in glycemia (week 12 minus baseline) to predict fold changes of zinc transportera and metallothioneinb genes individually and within gene clustersc Predictor
Components
Overall P-value
Univariate component
Univariate P value
Model 1
Fasting glucose
Model 2
HOMA-IR
All genes Cluster 1d Cluster 2e Cluster 3f All genes Cluster 1d Cluster 2e Cluster 3f
NS NS NS NS NS NS NS NS
Zip10 ZnT6 – – Zip10 ZnT6 – –
0.001 0.003 – – 0.001 0.007 – –
a b c d e f
ZnT1, ZnT5, ZnT6, ZnT7, ZnT8, Zip1, Zip3, Zip7, Zip10. MT-1A and MT-2A. Gene clusters determined by principle component analysis. Cluster 1 – ZnT1, ZnT6, ZnT8 and Zip3. Cluster 2 – ZnT5, ZnT7, Zip1, Zip7 and Zip10. Cluster 3 – MT-1A and MT-2A.
M. Foster et al. / Journal of Trace Elements in Medicine and Biology 28 (2014) 448–452
Discussion The present trial in postmenopausal women with Type 2 DM explored the effects of zinc, with and without n-3 PUFA supplementation, on HbA1c, serum glucose and insulin concentrations, and HOMA-IR; and the expression of a variety of zinc transporters and MT. No significant differences were observed between groups, however in statistical modeling of the outcome measures the fold changes in Zip10, and to a lesser extent ZnT6, were predicted by the changes in both HOMA-IR and serum glucose concentrations. The zinc transporter gene expression profile observed in the present study in Type 2 DM is comparable to our previous report in healthy participants [11], with ZnT7 and Zip1 being the most abundantly expressed transporters, while ZnT8 expression was variable. In participants with Type 2 DM we reported a range of bivariate relationships between zinc transporters, indicating coordination in zinc transporter gene expression, and showed that some relationships were determined by zinc status [9]. For instance, zinc supplementation was found to abolish the association between ZnT5 and Zip10 mRNA, which was observed in un-supplemented individuals. ZIP10 belongs to the Zip (SLC39) class of transporters that increase the cytoplasmic concentration of zinc via influx from the extracellular space or by efflux from intracellular vesicles. The expression of Zip10 transcripts has been demonstrated in pancreatic ␣- [12] and - [13] cells, supporting a possible role for ZIP10 in glucose homeostasis. ZIP10 has been shown to localize to the plasma membrane and, under zinc deficient conditions, to intracellular membranes [14]. The nutritional regulation of Zip10 expression appears to display tissue specificity; in murine brain and hepatic tissues, Zip10 mRNA and protein expression is increased substantially as a result of consuming a zinc deficient diet [14], however in testicular tissue ZIP10 protein abundance but not transcript expression is decreased as a result of zinc depletion [15]. In addition to regulation by dietary zinc, zinc transporters may be regulated by a variety of hormones and cytokines [7]; however little is known about the physiological mechanisms of Zip10 regulation. In this group of participants we observed previously that circulating cytokines, namely IL-6 concentrations, were positively related to the expression levels of zinc transporters including Zip10, such that each unit increase in IL-6 produced an 8–15% increase in the expression of Zip10 [9]. In isolated breast cancer cells treated with glucose concentrations equivalent to hyperglycemia in humans, the expression of Zip10 is reported to be up-regulated with a concomitant increase in cellular zinc concentrations [16]. Based on these observations, together with our finding that serum glucose predicts the fold change in Zip10 expression, it is plausible to hypothesize that the expression of Zip10 is regulated by the concentrations of IL-6 and glucose in serum, two metabolic features of Type 2 DM. ZnT6 functions in transporting cytoplasmic zinc into the Golgi apparatus and other vesicular compartments [17]. ZnT6 was shown to form heterodimers with ZnT5 in the early secretory pathway [18]. In the present study ZnT6 fold change was predicted by the change in serum glucose concentrations and HOMA-IR. There is, however, little or no other evidence currently to support a role for ZnT6 in glucose homeostasis. It is conceivable that through its action in transporting zinc into vesicular compartments ZnT6 may be involved in the metabolism of proinsulin and the subsequent insulin secretory mechanisms [19]. Single nucleotide polymorphisms in ZnT8 are associated with an increased risk of developing Type 2 DM [4,5]. Individuals with a variant (rs11558471) in ZnT8 exhibit higher glucose concentrations that are attenuated by an increase in the total intake of zinc from diet and supplements [20]. ZnT8 co-localizes with insulin in pancreatic islets and appears to be involved in both zinc accumulation
451
and regulation of insulin secretion in -cells [19]. The detection of ZnT8 in other endocrine cells [21], including ␣-cells [13], suggests that it may be involved in whole body glucose homeostasis [21]. In the present study, participants with Type 2 DM who exhibited ZnT8 mRNA expression were observed to have higher HbA1c levels at baseline than participants in whom ZnT8 was not expressed. This finding, in combination with our earlier report in this population of a positive association between ZnT8 expression and circulating TNF-␣ levels [9], further supports the notion of integration of zinc metabolism and risk factors for Type DM. Zinc exerts insulin-like effects by stimulating phosphorylation of the insulin receptor -subunit. Further, zinc can induce the PI3K/Akt insulin-signaling pathway by impacting molecular targets such as protein tyrosine phosphatases and lipid phosphatases [22,23]. Zinc has been shown to enhance the insulin-induced phosphorylation of Akt in cell culture [24] and it has been proposed that zinc supplementation may impact glucose metabolism by providing zinc to insulin-responsive cells [24], a suggestion that is supported by the present findings of relationships between Zip10, ZnT6, ZnT8 and glucose concentrations. The therapeutic effect of medications prescribed in the firstline treatment of Type 2 DM, by controlling the progression of the disease and normalizing metabolic responses to zinc, may have contributed to the lack of effect of zinc supplementation on any of the analyzed markers of glycemic control. The baseline serum glucose concentrations in the present study were in the reference range for all participants suggesting that the diabetic state was well managed. In a meta-analysis of controlled trials we showed previously that the glycemic responses to zinc supplementation were determined by the underlying health status of the participants, with healthy subjects showing no response to zinc while those with cardio-metabolic disease such as obesity and Type 2 DM, displaying a significant decrease in serum glucose concentrations [6] and an increase in high-density lipoprotein cholesterol concentrations [25]. The glycemic response to zinc in the present study in participants with Type 2 DM is comparable to that observed in healthy subjects [6] which supports the suggestion that supplementation with zinc has no effect on glycemic control beyond the effect of therapeutic agents in medically-controlled Type 2 DM. In addition to the underlying usage of medication by the participants, the sample size may have been too small to demonstrate differences between groups. Nevertheless the findings of the present study are novel in that little, if any, previous research has investigated the influence of zinc on zinc transporter mRNA expression in post-menopausal women with Type 2 DM. The significant predictive relationships between Zip10, ZnT6, serum glucose concentrations and HOMA-IR are preliminary, as is the finding of a relationship between HbA1c and ZnT8 expression, nevertheless they support an association between Type 2 DM and zinc homeostasis that requires further exploration.
Funding Financial support obtained from The Medical Advances Without Animals (MAWA) Trust; and Sydnovate, The University of Sydney. The funding bodies did not play any role in designing the study; in the collection, analysis, and interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication.
Conflict of interest None declared.
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Contributors MF and SS conceived the study, participated in its design and coordination, analysed the data, and drafted the manuscript. MF and AC collected data. PP performed the statistical analysis and commented on drafts of the manuscript. All authors read and approved the final manuscript. References [1] Foster M, Samman S. Zinc and redox signaling: perturbations associated with cardiovascular disease and diabetes mellitus. Antioxid Redox Signal 2010;13:1549–73. [2] Scott DA. Crystalline insulin. Biochem J 1934;28:1592–602. [3] Vallee BL. Biochemistry, physiology and pathology of zinc. Physiol Rev 1959;39:443–90. [4] Kirchhoff K, Machicao F, Haupt A, Schäfer SA, Tschritter O, Staiger H, et al. Polymorphisms in the TCF7L2, CDKAL1 and SLC30A8 genes are associated with impaired proinsulin conversion. Diabetologia 2008;51:597–601. [5] Sladek R, Rocheleau G, Rung J, Dina C, Shen L, Serre D, et al. A genomewide association study identifies novel risk loci for type 2 diabetes. Nature 2007;445:881–5. [6] Capdor J, Foster M, Petocz P, Samman S. Zinc and glycemic control: a metaanalysis of randomised placebo controlled supplementation trials in humans. J Trace Elem Med Biol 2013;27:137–42. [7] Lichten LA, Cousins RJ. Mammalian zinc transporters: nutritional and physiologic regulation. Ann Rev Nutr 2009;29:153–76. [8] Foster M, Petocz P, Caterson ID, Samman S. Effects of zinc and ␣-linolenic acid supplementation on glycemia and lipidemia in women with type 2 diabetes mellitus: a randomized, double-blind, placebo-controlled trial. J Diabetes Res Clin Metab 2013;2:3. [9] Foster M, Petocz P, Samman S. Inflammation markers predict zinc transporter gene expression in women with type 2 diabetes mellitus. J Nutr Biochem 2013;24:1655–61. [10] Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412–9.
[11] Foster M, Hancock D, Petocz P, Samman S. Zinc transporter genes are coordinately expressed in men and women independently of dietary or plasma zinc. J Nutr 2011;141:1195–201. [12] Gyulkhandanyan AV, Lu H, Lee SC, Bhattacharjee A, Wijesekara N, Fox JE, et al. Investigation of transport mechanisms and regulation of intracellular Zn2+ in pancreatic alpha-cells. J Biol Chem 2008;283:10184–97. [13] Gyulkhandanyan AV, Lee SC, Bikopoulos G, Dai F, Wheeler MB. The Zn2+ transporting pathways in pancreatic beta-cells: a role for the L-type voltage-gated Ca2+ channel. J Biol Chem 2006;281:9361–72. [14] Lichten LA, Ryu MS, Guo L, Embury J, Cousins RJ. MTF-1-mediated repression of the zinc transporter Zip10 is alleviated by zinc restriction. PLoS ONE 2011;6(6):e21526. [15] Croxford TP, McCormick NH, Kelleher SL. Moderate zinc deficiency reduces testicular Zip6 and Zip10 abundance and impairs spermatogenesis in mice. J Nutr 2011;141:359–65. [16] Takatani-Nakase T, Matsui C, Maeda S, Kawahara S, Takahashi K. High glucose level promotes migration behavior of breast cancer cells through zinc and its transporters. PLoS ONE 2014;9(2):e90136. [17] Huang L, Kirschke CP, Gitschier J. Functional characterization of a novel mammalian zinc transporter, ZnT6. J Biol Chem 2002;277:26389–95. [18] Fukunaka A, Suzuki T, Kurokawa Y, Yamazaki T, Fujiwara N, Ishihara K, et al. Demonstration and characterization of the heterodimerization of ZnT5 and ZnT6 in the early secretory pathway. J Biol Chem 2009;284:30798–806. [19] Chimienti F, Rutter GA, Wheeler MB, Wijesekara N. Zinc and diabetes. In: Rink L, editor. Zinc in human health, 76. Amsterdam: IOS Press; 2011. p. 493–513. [20] Kanoni S, Nettleton JA, Hivert MF, Ye Z, van Rooij FJ, Shungin D, et al. Total zinc intake may modify the glucose-raising effect of a zinc transporter (SLC30A8) variant: a 14-cohort meta-analysis. Diabetes 2011;60:2407–16. [21] Huang L. Zinc and its transporters, pancreatic -cells, and insulin metabolism. Vitam Horm 2014;95:365–90. [22] Taylor CG. Zinc, the pancreas, and diabetes: insights from rodent studies and future directions. Biometals 2005;18:305–12. [23] Jansen J, Karges W, Rink L. Zinc and diabetes: clinical links and molecular mechanisms. J Nutr Biochem 2009;20:399–417. [24] Jansen J, Rosenkranz E, Overbeck S, Warmuth S, Mocchegiani E, Giacconi R, et al. Disturbed zinc homeostasis in diabetic patients by in vitro and in vivo analysis of insulinomimetic activity of zinc. J Nutr Biochem 2012;23:1458–66. [25] Foster M, Petocz P, Samman S. Effects of zinc on plasma lipoprotein cholesterol concentrations in humans: a meta-analysis of randomised controlled trials. Atherosclerosis 2010;210:344–52.
Contents lists available at ScienceDirect
Journal of Trace Elements in Medicine and Biology journal homepage: www.elsevier.de/jtemb
ISTERH Conference Proceedings
Zinc transporter gene expression and glycemic control in post-menopausal women with Type 2 diabetes mellitus Meika Foster a , Anna Chu a , Peter Petocz b , Samir Samman a,∗ a b
Discipline of Nutrition & Metabolism, School of Molecular Bioscience, University of Sydney, NSW 2006, Australia Department of Statistics, Macquarie University, NSW 2109, Australia
a r t i c l e
i n f o
Keywords: Glucose Insulin Zinc transporter Gene expression Type 2 diabetes mellitus
a b s t r a c t Type 2 diabetes mellitus (DM) is associated often with underlying zinc deficiency and nutritional supplements such as zinc may be of therapeutic benefit in the disease. In a randomized, double-blind, placebo-controlled, 12-week trial in postmenopausal women (n = 48) with Type 2 DM we investigated the effects of supplementation with zinc (40 mg/d) and flaxseed oil (FSO; 2 g/d) on the gene expression of zinc transporters (ZnT1, ZnT5, ZnT6, ZnT7, ZnT8, Zip1, Zip3, Zip7, and Zip10) and metallothionein (MT-1A, and MT-2A), and markers of glycemic control (glucose, insulin, glycosylated hemoglobin [HbA1c]). The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated. No significant effects of zinc or FSO supplementation were observed on glycemic marker concentrations, HOMA-IR or fold change over 12 weeks in zinc transporter and metallothionein gene expression. In multivariate analysis, the change over 12 weeks in serum glucose concentrations (P = 0.001) and HOMA-IR (P = 0.001) predicted the fold change in Zip10. In secondary analysis, marginal statistical significance was observed with the change in both serum glucose concentrations (P = 0.003) and HOMA-IR (P = 0.007) being predictive of the fold change in ZnT6. ZnT8 mRNA expression was variable; HbA1c levels were higher (P = 0.006) in participants who exhibited ZnT8 expression compared to those who did not. The significant predictive relationships between Zip10, ZnT6, serum glucose and HOMA-IR are preliminary, as is the relationship between HbA1c and ZnT8; nevertheless the observations support an association between Type 2 DM and zinc homeostasis that requires further exploration. © 2014 Elsevier GmbH. All rights reserved.
Introduction Zinc dyshomeostasis and increased levels of oxidative stress play major roles in the pathogenesis of Type 2 diabetes mellitus (DM) [1]. Zinc is known to elicit insulin-like effects and it is this property that is most likely affected by the alterations in zinc distribution and metabolism associated with DM. Zinc deficiency associated with DM may impair the ability of zinc to induce the expression of zinc binding proteins, namely metallothionein (MT), and thereby increase the risk of oxidative stress-induced damage. Other critical pathways that are affected in DM and which are influenced by zinc include those of lipid metabolism, inflammation and insulin signalling [1]. Under normal conditions zinc is found throughout the pancreas, where it forms an integral component of the insulin crystalline structure [2], serving to stabilize the
∗ Corresponding author at: Department of Human Nutrition, University of Otago, PO Box 56, Dunedin 9054, New Zealand. E-mail address: [email protected] (S. Samman). http://dx.doi.org/10.1016/j.jtemb.2014.07.012 0946-672X/© 2014 Elsevier GmbH. All rights reserved.
insulin granule by rendering it less soluble [3]. Zinc transporter 8 (ZnT8) is responsible for delivering zinc ions from the cytoplasm of pancreatic -cells to insulin granules, which are subsequently secreted as a zinc-rich complex. Recent evidence suggests that single nucleotide polymorphisms in the ZnT8 gene are associated with impaired proinsulin conversion [4] and an increased risk of developing Type 2 DM [5]. Perturbed zinc homeostasis in DM appears to lead to a state of conditioned (secondary) zinc deficiency, evidenced in part by hyperzincuria that is reported to be present in the disease, and therefore zinc replenishment may exert a favourable effect. In a meta-analysis of randomised controlled trials that was conducted to determine the effect of zinc on markers of glycemic control, we reported a reduction in fasting serum glucose concentrations and a tendency for glycosylated hemoglobin (HbA1c) to decrease after zinc supplementation [6]. The interaction between glycemic markers and the gene expression of zinc transporters in humans is unclear. The aim of the present study is to examine the relationships between markers of glycemic control and the gene expression of MT and specific zinc transporters in women with Type 2 DM.
M. Foster et al. / Journal of Trace Elements in Medicine and Biology 28 (2014) 448–452
Zinc transporters were selected to canvass import and export functions across both the plasma and intracellular vesicular membranes and/or because they had been shown to be zinc-responsive in previous studies in humans, animal models and cell culture systems [7]. Methods and materials The trial design and participant details have been reported previously in papers exploring the effects of zinc and flaxseed oil (FSO) supplementation on markers of lipidemia and glycemia [8] and the relationships between zinc transporter and MT gene expression and inflammation [9]. In the present study we undertook a secondary analysis to determine the relationship between markers of glycemia and the gene expression of zinc transporters. Briefly, women were enrolled in the trial if they were post-menopausal (no menses for >12 mo) with Type 2 DM, and had a glomerular filtration rate and micro-albumin/creatinine ratio in the normal range. Exclusion criteria were: the use of insulin; smoking; and diagnosis with any current major illness other than DM. The Human Research Ethics Committee of the University of Sydney approved the study protocol and all participants provided written informed consent. The protocol was registered at http://www.ClinicalTrials.gov, with the identifier NCT01505803. The study was a randomized, double-blind, placebo-controlled trial conducted over 12 weeks. Upon enrolment, 48 participants were randomized into four equal groups to receive 40 mg/d elemental zinc, 2 g/d FSO, both zinc and FSO, or placebo. Venous blood samples were collected at 4-weekly intervals from participants after an overnight fast of at least 10 h. Cell preparation tubes (CPT vacutainers; Becton Dickinson) were used for the isolation of peripheral blood mononuclear cells (PBMC), serum gel tubes for glucose and insulin analyses, EDTA tubes for analysis of HbA1c, and trace metal tubes (Becton Dickinson) for plasma zinc analysis. Insulin resistance was estimated using the homeostasis model assessment (HOMA-IR) calculation [10].
449
Table 1 Biomarkers of glycemic control at baseline and week 12 in participants who were supplemented with zinc (n = 23) or not supplemented with zinc (n = 20).
Glucose (mmol/L) All Zn Control HbA1c (%) All Zn Control Insulin (pmol/L) All Zn Control HOMA-IR All Zn Control
Baseline
Week 12
Change
6.94 ± 0.26 6.77 ± 0.17 7.15 ± 0.53
6.87 ± 0.25 7.00 ± 0.66
0.11 ± 0.17 −0.16 ± 0.22
6.68 ± 0.15 6.55 ± 0.09 6.83 ± 0.30
6.73 ± 0.12 6.83 ± 0.32
0.18 ± 0.09 −0.01 ± 0.07
68.5 ± 5.51 63.0 ± 8.18 74.8 ± 7.18
69.8 ± 10.20 68.9 ± 4.95
3.52 ± 0.32 3.17 ± 0.43 3.93 ± 0.47
3.54 ± 0.49 3.53 ± 0.37
6.78 ± 5.32 −5.9 ± 5.22
0.36 ± 0.28 −0.40 ± 0.33
Data expressed as mean ± SE. HbA1c, glycosylated haemoglobin; HOMA-IR, homeostasis model of assessment–insulin resistance. Reference ranges for outcome measures are: glucose, 3.0–7.7 mmol/L; insulin, 10–96 pmol/L; HbA1c, 3.5–6.0%.
mRNA and participants in whom ZnT8 mRNA was not expressed were conducted using unpaired student t-tests. Principal component analysis was used to identify “clusters” of zinc transporter and MT gene expression, and multivariate and univariate ANOVA models were used to determine whether the glycemic markers (serum glucose, serum insulin, HOMA-IR, HbA1c) predicted any of the specific zinc transporter or MT mRNA or any of the identified clusters. Statistical analyses were carried out using SPSS v18. P < 0.01 was interpreted as statistically significant, with the exception that a conservative value of P < 0.001 was adopted for multivariate and univariate analyses due to the large number of test results under investigation. Results
Zinc transporter and metallothionein gene expression The method for measuring zinc transporter and MT mRNA expression has been described previously [9,11]. In brief, PBMC from individual samples were extracted and total RNA was prepared (Applied Biosystems-Life Technologies Australia Pty Ltd, Victoria, Australia) and reverse transcribed into cDNA (InvitrogenLife Technologies Australia Pty Ltd, Victoria, Australia) using commercially available kits. RNA integrity was assessed. Purity and yield of the isolated RNA were determined by UV spectrophotometry, with all samples generating an A260:A280 ratio within the range of 1.8–2.1. RNA integrity was verified by ethidium bromide staining after 1% denaturing agarose gel electrophoresis. Relative quantification of zinc transporter mRNA (ZnT1, ZnT5, ZnT6, ZnT7, ZnT8, Zip1, Zip3, Zip7, and Zip10), and MT (MT-1A, and MT-2A) was conducted using Taqman real-time PCR (ABI 7500 Fast Sequence Detection System; Applied Biosystems-Life Technologies Australia Pty Ltd, Victoria, Australia). Expression levels were normalized to 18S rRNA and quantified using the CP method, and fold change was quantified using the CP method. Statistical analysis Differences in the concentrations of biochemical measures over time within each treatment group were assessed using multivariate analysis. Post-hoc investigations using student t-tests were undertaken to compare the results of all participants who received zinc supplements with all participants who were not supplemented with zinc. Comparisons between participants who expressed ZnT8
Forty-three participants completed the trial and were included in the statistical analysis. The mean age and BMI were, respectively, 65.0 ± 7.8 y (mean ± SD) and 28.6 ± 5.1 kg/m2 . The plasma zinc concentration of participants at baseline was 12.8 ± 0.3 mol/L (mean ± SE) and within the reference range (10–18 mol/L). Serum concentrations of the glycemic measures were within their respective reference intervals, except for HbA1c, which was above the normal range (Table 1). Significant increases in plasma zinc were observed over time in the groups supplemented with zinc and both zinc and FSO (P = 0.002 and P = 0.019, respectively), but not in the groups supplemented with FSO alone or placebo. There were no statistically significant effects of zinc supplementation on HbA1c, serum glucose and insulin concentrations, or HOMA-IR when analysed by treatment group [8]; nor when grouped according to whether participants received (n = 23) or did not receive (n = 20) zinc as part of their intervention (Table 1). There were no significant differences in the baseline expression of any of the zinc transporter or MT mRNA in participants who received zinc compared to those who did not receive zinc as part of their intervention [9]. ZnT8 mRNA expression was detected only in 21 participants; compared to participants in whom ZnT8 mRNA was not expressed, participants who expressed ZnT8 mRNA were observed to have higher HbA1c levels (6.75% vs. 6.31%; P = 0.006). There were no significant differences between baseline and week 12 zinc transporter (including ZnT6 and Zip10; Fig. 1), and MT mRNA expression in participants, irrespective of zinc
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Fig. 1. Relative mRNA expression of ZnT6 (Panel A) and Zip10 (Panel B) at baseline and week 12 in participants who were supplemented with zinc (n = 23) or not supplemented with zinc (n = 20). In multivariate analysis, the change in serum glucose concentrations and HOMA-IR predicted the fold change in Zip10. In secondary analysis statistical significance was observed with the change in both serum glucose concentrations and HOMA-IR being predictive of the fold change in ZnT6 and Zip10 (see details in Table 2). Values are shown as mRNA per 106 18S rRNA, and expressed as mean ± SE.
supplementation. No significant up- or down-regulation of gene expression in response to zinc supplementation was observed. In univariate analysis, the change in both serum glucose concentrations (P = 0.001) and HOMA-IR (P = 0.001) predicted the fold change in Zip10 (Table 2). Principal component analysis of expression levels at baseline revealed 3 clusters, each containing zinc transporter or MT mRNA, that behaved in a similar manner. The clusters were identified as cluster 1: ZnT5, ZnT7, Zip1, Zip7
and Zip10; cluster 2: ZnT1, ZnT6, ZnT8 and Zip3; and cluster 3: MT-1A and MT-2A. A multivariate ANOVA model was used to determine the relationships between glycemic markers and mRNA expression within the clusters. No significant relationships were observed by multivariate ANOVA, however univariate analysis of cluster 2 revealed marginal statistical significance with the change in both serum glucose (P = 0.003) and HOMA-IR (P = 0.007) being predictive of the fold change in ZnT6 (Table 2).
Table 2 Multivariate analysis of variance models using change in glycemia (week 12 minus baseline) to predict fold changes of zinc transportera and metallothioneinb genes individually and within gene clustersc Predictor
Components
Overall P-value
Univariate component
Univariate P value
Model 1
Fasting glucose
Model 2
HOMA-IR
All genes Cluster 1d Cluster 2e Cluster 3f All genes Cluster 1d Cluster 2e Cluster 3f
NS NS NS NS NS NS NS NS
Zip10 ZnT6 – – Zip10 ZnT6 – –
0.001 0.003 – – 0.001 0.007 – –
a b c d e f
ZnT1, ZnT5, ZnT6, ZnT7, ZnT8, Zip1, Zip3, Zip7, Zip10. MT-1A and MT-2A. Gene clusters determined by principle component analysis. Cluster 1 – ZnT1, ZnT6, ZnT8 and Zip3. Cluster 2 – ZnT5, ZnT7, Zip1, Zip7 and Zip10. Cluster 3 – MT-1A and MT-2A.
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Discussion The present trial in postmenopausal women with Type 2 DM explored the effects of zinc, with and without n-3 PUFA supplementation, on HbA1c, serum glucose and insulin concentrations, and HOMA-IR; and the expression of a variety of zinc transporters and MT. No significant differences were observed between groups, however in statistical modeling of the outcome measures the fold changes in Zip10, and to a lesser extent ZnT6, were predicted by the changes in both HOMA-IR and serum glucose concentrations. The zinc transporter gene expression profile observed in the present study in Type 2 DM is comparable to our previous report in healthy participants [11], with ZnT7 and Zip1 being the most abundantly expressed transporters, while ZnT8 expression was variable. In participants with Type 2 DM we reported a range of bivariate relationships between zinc transporters, indicating coordination in zinc transporter gene expression, and showed that some relationships were determined by zinc status [9]. For instance, zinc supplementation was found to abolish the association between ZnT5 and Zip10 mRNA, which was observed in un-supplemented individuals. ZIP10 belongs to the Zip (SLC39) class of transporters that increase the cytoplasmic concentration of zinc via influx from the extracellular space or by efflux from intracellular vesicles. The expression of Zip10 transcripts has been demonstrated in pancreatic ␣- [12] and - [13] cells, supporting a possible role for ZIP10 in glucose homeostasis. ZIP10 has been shown to localize to the plasma membrane and, under zinc deficient conditions, to intracellular membranes [14]. The nutritional regulation of Zip10 expression appears to display tissue specificity; in murine brain and hepatic tissues, Zip10 mRNA and protein expression is increased substantially as a result of consuming a zinc deficient diet [14], however in testicular tissue ZIP10 protein abundance but not transcript expression is decreased as a result of zinc depletion [15]. In addition to regulation by dietary zinc, zinc transporters may be regulated by a variety of hormones and cytokines [7]; however little is known about the physiological mechanisms of Zip10 regulation. In this group of participants we observed previously that circulating cytokines, namely IL-6 concentrations, were positively related to the expression levels of zinc transporters including Zip10, such that each unit increase in IL-6 produced an 8–15% increase in the expression of Zip10 [9]. In isolated breast cancer cells treated with glucose concentrations equivalent to hyperglycemia in humans, the expression of Zip10 is reported to be up-regulated with a concomitant increase in cellular zinc concentrations [16]. Based on these observations, together with our finding that serum glucose predicts the fold change in Zip10 expression, it is plausible to hypothesize that the expression of Zip10 is regulated by the concentrations of IL-6 and glucose in serum, two metabolic features of Type 2 DM. ZnT6 functions in transporting cytoplasmic zinc into the Golgi apparatus and other vesicular compartments [17]. ZnT6 was shown to form heterodimers with ZnT5 in the early secretory pathway [18]. In the present study ZnT6 fold change was predicted by the change in serum glucose concentrations and HOMA-IR. There is, however, little or no other evidence currently to support a role for ZnT6 in glucose homeostasis. It is conceivable that through its action in transporting zinc into vesicular compartments ZnT6 may be involved in the metabolism of proinsulin and the subsequent insulin secretory mechanisms [19]. Single nucleotide polymorphisms in ZnT8 are associated with an increased risk of developing Type 2 DM [4,5]. Individuals with a variant (rs11558471) in ZnT8 exhibit higher glucose concentrations that are attenuated by an increase in the total intake of zinc from diet and supplements [20]. ZnT8 co-localizes with insulin in pancreatic islets and appears to be involved in both zinc accumulation
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and regulation of insulin secretion in -cells [19]. The detection of ZnT8 in other endocrine cells [21], including ␣-cells [13], suggests that it may be involved in whole body glucose homeostasis [21]. In the present study, participants with Type 2 DM who exhibited ZnT8 mRNA expression were observed to have higher HbA1c levels at baseline than participants in whom ZnT8 was not expressed. This finding, in combination with our earlier report in this population of a positive association between ZnT8 expression and circulating TNF-␣ levels [9], further supports the notion of integration of zinc metabolism and risk factors for Type DM. Zinc exerts insulin-like effects by stimulating phosphorylation of the insulin receptor -subunit. Further, zinc can induce the PI3K/Akt insulin-signaling pathway by impacting molecular targets such as protein tyrosine phosphatases and lipid phosphatases [22,23]. Zinc has been shown to enhance the insulin-induced phosphorylation of Akt in cell culture [24] and it has been proposed that zinc supplementation may impact glucose metabolism by providing zinc to insulin-responsive cells [24], a suggestion that is supported by the present findings of relationships between Zip10, ZnT6, ZnT8 and glucose concentrations. The therapeutic effect of medications prescribed in the firstline treatment of Type 2 DM, by controlling the progression of the disease and normalizing metabolic responses to zinc, may have contributed to the lack of effect of zinc supplementation on any of the analyzed markers of glycemic control. The baseline serum glucose concentrations in the present study were in the reference range for all participants suggesting that the diabetic state was well managed. In a meta-analysis of controlled trials we showed previously that the glycemic responses to zinc supplementation were determined by the underlying health status of the participants, with healthy subjects showing no response to zinc while those with cardio-metabolic disease such as obesity and Type 2 DM, displaying a significant decrease in serum glucose concentrations [6] and an increase in high-density lipoprotein cholesterol concentrations [25]. The glycemic response to zinc in the present study in participants with Type 2 DM is comparable to that observed in healthy subjects [6] which supports the suggestion that supplementation with zinc has no effect on glycemic control beyond the effect of therapeutic agents in medically-controlled Type 2 DM. In addition to the underlying usage of medication by the participants, the sample size may have been too small to demonstrate differences between groups. Nevertheless the findings of the present study are novel in that little, if any, previous research has investigated the influence of zinc on zinc transporter mRNA expression in post-menopausal women with Type 2 DM. The significant predictive relationships between Zip10, ZnT6, serum glucose concentrations and HOMA-IR are preliminary, as is the finding of a relationship between HbA1c and ZnT8 expression, nevertheless they support an association between Type 2 DM and zinc homeostasis that requires further exploration.
Funding Financial support obtained from The Medical Advances Without Animals (MAWA) Trust; and Sydnovate, The University of Sydney. The funding bodies did not play any role in designing the study; in the collection, analysis, and interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication.
Conflict of interest None declared.
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Contributors MF and SS conceived the study, participated in its design and coordination, analysed the data, and drafted the manuscript. MF and AC collected data. PP performed the statistical analysis and commented on drafts of the manuscript. All authors read and approved the final manuscript. References [1] Foster M, Samman S. Zinc and redox signaling: perturbations associated with cardiovascular disease and diabetes mellitus. Antioxid Redox Signal 2010;13:1549–73. [2] Scott DA. Crystalline insulin. Biochem J 1934;28:1592–602. [3] Vallee BL. Biochemistry, physiology and pathology of zinc. Physiol Rev 1959;39:443–90. [4] Kirchhoff K, Machicao F, Haupt A, Schäfer SA, Tschritter O, Staiger H, et al. Polymorphisms in the TCF7L2, CDKAL1 and SLC30A8 genes are associated with impaired proinsulin conversion. Diabetologia 2008;51:597–601. [5] Sladek R, Rocheleau G, Rung J, Dina C, Shen L, Serre D, et al. A genomewide association study identifies novel risk loci for type 2 diabetes. Nature 2007;445:881–5. [6] Capdor J, Foster M, Petocz P, Samman S. Zinc and glycemic control: a metaanalysis of randomised placebo controlled supplementation trials in humans. J Trace Elem Med Biol 2013;27:137–42. [7] Lichten LA, Cousins RJ. Mammalian zinc transporters: nutritional and physiologic regulation. Ann Rev Nutr 2009;29:153–76. [8] Foster M, Petocz P, Caterson ID, Samman S. Effects of zinc and ␣-linolenic acid supplementation on glycemia and lipidemia in women with type 2 diabetes mellitus: a randomized, double-blind, placebo-controlled trial. J Diabetes Res Clin Metab 2013;2:3. [9] Foster M, Petocz P, Samman S. Inflammation markers predict zinc transporter gene expression in women with type 2 diabetes mellitus. J Nutr Biochem 2013;24:1655–61. [10] Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412–9.
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