The role of cadmium in obesity and diabetes

Science of the Total Environment 601–602 (2017) 741–755

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Review

The role of cadmium in obesity and diabetes☆ Alexey A. Tinkov a,b,c,⁎, Tommaso Filippini k, Olga P. Ajsuvakova d, Jan Aaseth e,f, Yordanka G. Gluhcheva g, Juliana M. Ivanova h, Geir Bjørklund i, Margarita G. Skalnaya d, Eugenia R. Gatiatulina b,j, Elizaveta V. Popova b,l, Olga N. Nemereshina b, Marco Vinceti k, Anatoly V. Skalny a,c,d a

Yaroslavl State University, Yaroslavl, Russia Orenburg State Medical University, Orenburg, Russia RUDN University, Moscow, Russia d Orenburg State Pedagogical University, Orenburg, Russia e Department of Public Health, Hedmark University of Applied Sciences, Elverum, Norway f Research Department, Innlandet Hospital Trust, Brumunddal, Norway g Institute of Experimental Morphology, Pathology and Anthropology with Museum, Bulgarian Academy of Sciences, Sofia, Bulgaria h Faculty of Medicine, Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria i Council for Nutritional and Environmental Medicine, Mo i Rana, Norway j South-Ural State Medical University, Chelyabinsk, Russia k CREAGEN, Environmental, Genetic and Nutritional Epidemiology Research Center, University of Modena and Reggio Emilia, Modena, Italy l St Joseph University in Tanzania, St Joseph College of Health Sciences, Dar es salaam, Tanzania b c

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Human data on the association between Cd exposure and obesity are contradictory. • Laboratory studies demonstrate that Cd exposure causes adipose tissue dysfunction. • Cd-induced adipose tissue dysfunction promotes insulin resistance without obesity. • Human and laboratory studies indicate the role of Cd in diabetes.

a r t i c l e

i n f o

Article history: Received 14 April 2017 Received in revised form 23 May 2017 Accepted 24 May 2017 Available online xxxx Editor: D. Barcelo Keywords: Cadmium Adipose tissue

a b s t r a c t Multiple studies have shown an association between environmental exposure to hazardous chemicals including toxic metals and obesity, diabetes, and metabolic syndrome. At the same time, the existing data on the impact of cadmium exposure on obesity and diabetes are contradictory. Therefore, the aim of the present work was to review the impact of cadmium exposure and status on the risk and potential etiologic mechanisms of obesity and diabetes. In addition, since an effect of cadmium exposure on incidence of diabetes mellitus and insulin resistance was suggested by several epidemiologic studies, we carried out a meta-analysis of all studies assessing risk of prevalence and incidence of diabetes. By comparing the highest versus the lowest cadmium exposure category, we found a high risk of diabetes incidence (odds ratio = 1.38, 95% confidence interval 1.12–1.71), which was higher for studies using urine as exposure assessment. On the converse, results of epidemiologic studies linking cadmium exposure and overweight or obesity are far less consistent and even conflicting, also depending on

☆ This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. ⁎ Corresponding author at: Yaroslavl State University, Yaroslavl, Russia. E-mail address: [email protected] (A.A. Tinkov).

http://dx.doi.org/10.1016/j.scitotenv.2017.05.224 0048-9697/© 2017 Elsevier B.V. All rights reserved.

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Insulin resistance Obesity Diabetes

differences in exposure levels and the specific marker of exposure (blood, urine, hair, nails). In turn, laboratory studies demonstrated that cadmium adversely affects adipose tissue physiopathology through several mechanisms, thus contributing to increased insulin resistance and enhancing diabetes. However, intimate biological mechanisms linking Cd exposure with obesity and diabetes are still to be adequately investigated. © 2017 Elsevier B.V. All rights reserved.

Contents 1. 2.

Introduction . . . . . . . . . . . . Cadmium as an environmental toxicant 2.1. Cd and inflammation . . . . . 2.2. Cd and oxidative stress . . . . 2.3. Cadmium and genotoxicity . . 3. Cadmium and obesity . . . . . . . . 3.1. Human studies . . . . . . . . 3.2. Experimental data . . . . . . 4. Cadmium and type 2 diabetes mellitus 4.1. Human studies . . . . . . . . 4.2. Experimental data . . . . . . 5. Conclusion . . . . . . . . . . . . . Conflict of interest . . . . . . . . . . . . References. . . . . . . . . . . . . . . .

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1. Introduction Obesity and diabetes mellitus type 2 have reached epidemic proportions on the border between XX and XXI centuries (James et al., 2001; Lam and LeRoith, 2012). In particular, the prevalence of obesity among American adults has doubled from 1980 to 2000, accounting for one third of the population (Ogden et al., 2014). Moreover, in 2013, every third person worldwide had excessive body weight (overweight or obesity) (Hruby and Hu, 2015). Correspondingly, the number of diabetics in 2013 was neatly 382 million, and it is expected to increase to 592 million in 2035 (Winer and Sowers, 2004). Due to an extremely high prevalence and association with metabolic disturbances, obesity has a significant socioeconomic impact, being associated with 21% of all health expenditures in the USA ($190 billion/year) (Hruby and Hu, 2015). In turn, according to 2012 estimates, the total cost of DM2 in USA was $245 billion, being characterized by a 41% increase in comparison to the 2007 (ADA, 2013). Obesity is associated by increased adipose tissue mass and adipocyte dysfunction (Hajer et al., 2008), being accompanied by increased production of proinflammatory adipokines (Fantuzzi, 2005; Weisberg et al., 2003; Wellen and Hotamisligil, 2003), oxidative stress (Furukawa et al., 2004), endoplasmic reticulum stress (Özcan et al., 2004), and insulin resistance (Maury and Brichard, 2010). Such mechanisms mediate a tight interaction between obesity and diabetes, that resulted in the introduction of the term “diabesity” (Farag and Gaballa, 2011; Schmidt and Duncan, 2003). Moreover, a complex of pathologies including obesity, hyperglycemia, arterial hypertension and dyslipoproteinemia was clustered and termed “metabolic syndrome” (Eckel et al., 2010). Multiple attempts have been made to assess the causes of diabesity and metabolic syndrome epidemics. In particular, it has been proposed that the increased incidence of both diabetes and obesity may be associated with the increased number of sweeteners, sedentary lifestyle, stress, nutrient deficiencies (Hyman, 2014). These observations are in general in agreement with the initial hypothesis of the role of positive caloric balance in obesity, diabetes, and metabolic syndrome in general (Hyman, 2014; Roberts et al., 2013). However, recent studies have revealed a significant association between environmental pollution and obesity epidemics (Madrigano et al., 2010). The possible role of certain

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chemical toxins of environmental in the etiology of obesity epidemics was proposed recently in the latest years (Baillie-Hamilton, 2002). Further studies have demonstrated the impact of environmental pollution on the incidence of diabetes and metabolic syndrome (Andersen et al., 2012; Eze et al., 2015). Moreover, it has been proposed that differential response of the human organism to environmental pollution even in terms of similar exposure patterns is indicative of the presence of gene-environment interaction that may promote the development of metabolic syndrome (Andreassi, 2009). Toxic metals and metalloids also seem to be involved in MetS pathophysiology (Wang et al., 2014). Thus, it has been demonstrated that metabolic syndrome is associated with mercury (Chung et al., 2015; Eom et al., 2014; Park et al., 2013; Tinkov et al., 2015), lead (Lee et al., 2013; Park et al., 2006; Rhee et al., 2013), and arsenic (Chen et al., 2012; Wang et al., 2007; Wang et al., 2010) exposure. Cadmium is a heavy metal that also refers to endocrine disrupting chemicals, having a special impact on the functioning of reproductive organs, including testes, placenta (Takiguchi and Yoshihara, 2005), and ovaries (Henson and Chedrese, 2004). The mechanisms of toxicity of Cd also include induction of oxidative and endoplasmic reticulum stress, inflammatory response (Moulis and Thévenod, 2010; Thévenod and Lee, 2013), genotoxicity (Filipič, 2012; Schwerdtle et al., 2010), and interference with essential metals (especially zinc) (Moulis, 2010). Despite the well-documented role of endocrine disrupting chemicals, oxidative, endoplasmic reticulum stress, and inflammation in pathogenesis of obesity, diabetes and metabolic syndrome, the association between Cd exposure, diabetes, and especially obesity, as well as the underlying mechanisms are still unclear. Therefore, the primary objective of the study was to review the existing clinical and experimental data on the association between Cd exposure, body burden and obesity and diabetes in clinical and experimental studies, and the mechanisms linking Cd to these pathologies. 2. Cadmium as an environmental toxicant Cadmium (Cd) is released in the environment by natural and anthropogenic activities. It is utilized for corrosion protection of steel (cadmium plating), as solder and weld metal in alloys, polyvinyl chloride plastics, as pigments in paint colours, different types of paint and glazes,

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fertilizers (Cheraghi et al., 2012; de Vries and McLaughlin, 2013). Cd(II) compounds are found both in soil, drinking water, as well as in food (Türkdoğan et al., 2003). For the general population, food and cigarette smoke are the primary sources of Cd exposure. Cadmium-rich foods include seafood, liver, kidney, wild mushrooms, flaxseed, and cocoa powder. However, 80% of food-Cd comes from cereals, potatoes, and vegetables grown on contaminated soil (Olsson et al., 2002). From food, the average daily intake of Cd varies between 8 and 25 μg (Egan et al., 2007; Järup and Åkesson, 2009). Vegetarians and those who consume much seafood have a higher intake of Cd than other people have. For decades Cd has been recognized as an occupational and environmental risk factor, inducing multi organ dysfunction. The minimal risk levels (MRL) for acute and chronic inhalations are 0.00003 mg/m3, and 0.00001 mg/m3 respectively. The MRL for intermediate oral exposure is calculated to be 0.0005 mg/kg/day, while for chronic oral exposure is 0.0001 mg/kg/day. Kidneys, liver, bones, respiratory and reproductive systems are the main target of Cd intoxication. Cd has a biological half-life in the kidneys between 10 and 30 years. The Cd amount in urine (UCd) reflects the level in the kidneys. Cadmium can cause bone damage either via a direct effect on bone tissue or indirectly because of renal dysfunction (Järup and Åkesson, 2009). At higher Cd exposure severe (glomerular) kidney damage and bone disease (osteomalacia) may occur. There are also some indications that Cd can affect the fetal brain. In occupationally Cd-exposed workers, the US EPA has evaluated the risk of lung cancer at an air concentration of 6 ng Cd/m3 to be 1/100,000 (“low-risk level”) (US EPA, 2000). Individuals with iron deficiency, pregnant women, newborns and toddlers may have an increased uptake of Cd. The toxic effects of Cd in individuals also depend on the intake of zinc (Zn) and selenium (Se). The toxicology of cadmium has been extensively discussed by Nordberg et al. (2014) in their Handbook on the toxicology of metals. It exerts its toxic effects mainly through inflammation, oxidative stress and genotoxicity. 2.1. Cd and inflammation Increasing data show that in vivo and/or in vitro exposure to Cd results in activation of specific cell types (e.g. Kupffer cells in the liver), organ infiltration with neutrophils and enhanced release of proinflammatory and anti-inflammatory factors by monocytes/macrophages (Djokic et al., 2014; Kataranovski et al., 2009). Many inflammatory biomarkers, released upon Cd exposure have been linked to different diseases – atherosclerosis, cardiovascular diseases, etc. The effects of Cd on pro- and anti-inflammatory cytokines reveal the immunomodulatory role of the metal as well as its differential effects on cytokine production. Even in micromolar concentrations (1–10 μM) (Olszowski et al., 2012) Cd exhibits pro-inflammatory properties and up-regulates the expression of IL-1, IL-6, IL-8, TNF-α and different chemokines in various types of cells (Odewumi et al., 2015; Papa et al., 2014; Riemschneider et al., 2015; Cormet-Boyaka et al., 2012; Dong et al., 1998; Horiguchi et al., 1993, 2000; Souza et al., 2004). Of the immune system, cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS) are early response genes in the inflammatory process and are commonly used as inflammatory markers (Ramyaa et al., 2014). IL-10 is one of the key anti-inflammatory cytokines, responsible for the inhibition of pro-inflammatory cytokines, released from the monocytes/macrophages. Stimulated expression of IL-10 following treatment with 50 μM CdCl2 was observed in A549 lung cancer cells (Odewumi et al., 2015).

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oxidation/reduction to generate ROS directly, it can induce oxidative stress by different pathways (Cuypers et al., 2010). Cd has high affinity to sulfhydryl groups, therefore it can deplete the levels of the cellular antioxidants (glutathione (GSH), superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (Gpx)) in soft tissues (Cuypers et al., 2010; Ivanova et al., 2013). In vascular tissue, Cd can induce oxidative stress by activation of nicotinamide adenine dinucleotide phosphate (NADPH) oxidases and xanthine oxidase and uncoupling of endothelial nitric oxide synthase (eNOS) (Kukongviriyapan et al., 2016). Experimental data reveal that ROS, generated indirectly by Cd, could enhance lipid peroxidation. Malondialdehyde (MDA) is commonly used to monitor lipid peroxidation. Numerous studies demonstrate that Cd induces a significant increase in MDA levels in organs and blood of Cd-treated animal compared to the untreated control animals (Ivanova et al., 2013; Nemmiche et al., 2007). Djukić-Cosić et al. (2008) found a positive correlation between MDA levels and Fe content in liver of Cd-exposed mice. They confirmed the hypothesis that the generation of ROS via Fenton reaction could contribute to the Cd-induced LPO. According to Liu et al. (2009) Oxidative stress plays a major role in acute Cd poisoning while alterations in ROS-related gene expression during chronic treatment are less significant. Adaptation to chronic Cd exposure reduces ROS production, but damaged cells proliferate with inherent oxidative DNA lesions, potentially leading to tumorigenesis (Liu et al., 2009). In vitro studies show that low concentrations of Cd2+ trigger apoptosis, while higher concentrations induce necrosis (Messner et al., 2012). Experimental evidence indicates that apoptosis plays a significant role in acute and chronic Cd2+ intoxication. Cd2+ has been shown to induce apoptosis, as indicated by cell contraction, annexin V overexpression, reactive oxygen species (ROS) generation, DNA fragmentation, and cell cycle arrest, and through the activation of caspases 3, 7, 8 and 9 in different cells (Xie and Shaikh, 2006; Wang et al., 2016). 2.3. Cadmium and genotoxicity Studies on bacterial and mammalian cells demonstrate that Cd exerts mutagenic effect mainly by an indirect mechanism, which involves interaction with DNA repair processes (Hartwig, 1994). In mammalian cells exposed to UV light, Cd enhanced the mutation frequency (Hartwig and Beyersmann, 1989), inhibited the unscheduled DNA synthesis, and induced accumulation of DNA strand breaks and chromosomal aberrations. A single i.p. dose of Cd(II) chloride (5 mg/kg BW) significantly increased the chromosomal aberration in bone marrow cells of Swiss Albino mice (Jahangir et al., 2006). El-Habit and Abdel Moneim (2014) observed Cd-induced dose-dependent DNA damage in mouse bone marrow cells, a significant decrease in GSH level, and that LPO increased when the Cd dose increased. These results demonstrate that ROS generation could contribute to the Cd-induced genotoxicity. Claudio et al. (2016) reported that cadmium substantially increased the number of micronuclei and DNA strand breaks in blood and liver cells of intoxicated Wistar rats. Based on the reported in vitro and in vivo experiments two main molecular mechanisms of Cd-induced genotoxicity can be summarized. The first one is related to the effect of the toxic metal ion on the DNA repair processes and the second involves generation of ROS. The results on the genotoxicity of Cd in humans are controversial. One possible explanation for the conflicting data about the genotoxic effect of Cd in humans can be related to a difference in the dose of the toxic metal ion. Significant induction of micronuclei was reported for high levels of exposure to Cd (Nersesyan et al., 2016). 3. Cadmium and obesity

2.2. Cd and oxidative stress 3.1. Human studies The production of reactive oxygen species followed by the development of oxidative stress in the target organs is one of the mechanisms through which Cd exerts its toxicity. Although Cd cannot undergo

Data from the human studies on the interaction between Cd exposure and obesity are rather contradictory, varying from negative to

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positive. In particular, it has been demonstrated that blood cadmium levels were associated with higher BMI, waist and hip circumference in girls aged 8–15 years (Kim et al., 2015). It is also interesting that examination of indigenous women of a Torres Strait Island revealed a significant direct correlation between cadmium levels and waist circumference (r = 0.30; p = 0.02) but not BMI. The observed association was not affected by age adjustment (Haswell-Elkins et al., 2007). A detailed analysis of data from the NHANES 1999–2002 revealed a direct correlation between body mass index and waist circumference and urinary Cd levels. However, in the regression models incorporating various heavy metals the level of cadmium was inversely associated with the anthropometric indices of obesity (Padilla et al., 2010). Earlier we have detected a weak but significant correlation between hair Cd content and BMI values in women aged 22–35 years (Skalnaya et al., 2014). We have also demonstrated that serum Cd levels are associated with BMI values in women from Modena (Northern Italy community) (β = 1.16; p = 0.021 after adjustment for age, BMI, and energy intake), whereas no such association was revealed in men (β = 1.01; p = 0.538) or in the total cohort (β = 1.05; p = 0.136) (Filippini et al., 2016). Blood Cd levels were also significantly associated with BMI in type 2 diabetes mellitus patients (Akinloye et al., 2010). It is also notable that weight reduction (BMI (kg/m2) from 29.1 to 27 at p b 0.05) in obese Egyptian children taking part in a 2-Month Program of AntioxidantsMicronutrient-Rich Diet was associated with a significant reduction in urinary Cd levels (El-Soud et al., 2011). However, the changes observed in the last study may be related not only to reduced body weight but rather to the quality of the diet rich in micronutrients that may increase Cd excretion. It is also interesting, that blood Cd levels in obese males were significantly associated with osteoporosis, whereas such relationship was not significant in non-obese ones (Choi and Han, 2015). Surprisingly, women with normal pre-pregnancy BMI values with high urinary Cd concentration were characterized by a 2.15-fold increased risk of gestational diabetes mellitus (GDM) whereas those with high BMI and Cd values had 1.21-times higher risk of GDM, as compared to the respective BMI-groups (Romano et al., 2015). At the same time, a high number of human studies demonstrated a negative interaction between Cd exposure and anthropometric indices of obesity. Briefly, a recent dietary survey demonstrated that dietary Cd content was a negative predictor of BMI (p = 0.008) only in the crude linear regression model, but not after adjustment for total energy intake, sex, age, ethnicity and smoking (Kurzius-Spencer, 2013). Erythrocyte Cd content was slightly but significantly (r = −0.14; p b 0.001) inversely associated with BMI values in postmenopausal Swedish women (Rignell-Hydbom et al., 2009). Similarly, the association between blood Cd levels and BMI was significantly negative only in the middle tertile of Cd concentrations, but the overall trend was not significant (Nie et al., 2016). Similarly, multiple regression analysis performed in the database from NHANES 1999–2008 demonstrated a significant inverse association between urinary Cd and BMI values in children, teens, and smoking adults, but not in the non-smoking ones (Riederer et al., 2013). Examination of middle-aged residents of abandoned metal mines in Korea revealed a significant negative association between blood but not urinary Cd levels and BMI values (Son et al., 2015). The results of the study involving 3348 American Indian (aged 45–74 years) who participated in the Strong Heart Study in 1989–1991 also revealed a significant negative association between urinary Cd levels and BMI values (p for trend b 0.001) (Tellez-Plaza et al., 2013). Oppositely, certain studies failed to detect any significant association between the levels of Cd in the organism and excessive weight. Thus, no association (p = 0.92) between blood cadmium levels and BMI was detected in the CASPIAN-III Study (Kelishadi et al., 2013). Similarly, no effect of obesity on hair Cd levels was found in the healthy population of the Canary Islands (Gonzalez-Reimers et al., 2014) and from the Korea National Health and Nutrition Examination Survey 2010–2013 (Ahn

et al., 2016). A study performed in Malaysia also failed to detect any significant association between BMI and urinary Cd levels (Adnan et al., 2012). A recent European study demonstrated that non-smoking overweight mothers are characterized by slightly increased urinary Cd levels than those with normal body weight but also with obesity (Berglund et al., 2015). No significant relationship between blood cadmium and body fat was revealed (Park and Lee, 2013). Similarly, no correlation between body mass and blood Cd concentration was detected in children living in the regions with high and low rate of pollution (HuziorBałajewicz et al., 2001). Significantly higher levels of Cd were observed in adipose tissue of patients with uterine leiomyomas as compared to the control values. However, the association of adipose tissue metal levels with BMI was not significant (Qin et al., 2010). Examination of diabetic hemodialysis patients demonstrated that persons with different blood Cd levels were not characterized by a significant group difference in BMI (Yen et al., 2011). Therefore, the existing data demonstrate that Cd exposure may be both negatively and positively associated with overweight/obesity, or not have any significant impact on excessive weight gain. The existing contradictions between the results of the above mentioned studies may be at least partially mediated by the differences in the Cd exposure levels (reference level, environmental exposure, occupational exposure) as well as by the use of different markers for Cd exposure (blood, urine, hair, nails) in humans. 3.2. Experimental data Laboratory studies have confirmed the complex influence of Cd exposure on adipose tissue physiology and obesity pathogenesis (Table 1). A recent study demonstrated that Cd significantly reduced adipocyte size and increased macrophage infiltration of white adipose tissue through up-regulation of MCP-1 expression in metallothionein-null mice (Kawakami et al., 2013). These findings are in agreement with the earlier study by Kawakami and colleagues, who demonstrated significantly lowered adiponectin and leptin expression as well as decreased adipocyte size in MT-null mice in response to Cd treatment. Notably, adipocyte size recovered in 6 weeks after Cd withdrawal in MT-null mice, however, the expression of both adiponectin and leptin remained low (Kawakami et al., 2012). Six-week Cd intake with drinking water was associated with a non-significant tendency to increased body weight and adipocyte diameter, whereas both total number of insulin receptors and insulin receptor density on adipocytes was significantly decreased. At the same time, no significant effect of Cd exposure on GluT4 content on adipocyte membranes was detected (Ficková et al., 2003). Oral cadmium treatment in female rats resulted in a significantly lower body weight as compared to the control animals (Zhang et al., 2003). Therefore, modeling of Cd exposure in experimental animals did not result in obesity, but significantly impaired adipose tissue physiology in vivo. Cell culture studies demonstrated that incubation of adipocytes and progenitor cells with cadmium disrupts multiple metabolic pathways. In particular, an in vitro study of Cd toxicity in 3T3-L1 adipocytes revealed significantly decreased dose-dependent cell viability after Cd2+ exposure as assessed by MTT-assay and colony forming efficiency assay (Moon and Yoo, 2008). In vitro exposure of adipocytes to Cd resulted in a significant decrease in leptin, adiponectin, and resistin expression, being associated with decreased fatty acid synthesis and lipid degradation mediated by perilipin (Kawakami et al., 2013), being in agreement with the observation of dose-dependent decrease in leptin production in adipocytes incubated with CdCl2 (0.01, 0.1, 1.0, 10.0 mM) (Levy et al., 2000). These findings are in agreement with the earlier data of the authors. In particular, it has been demonstrated that Cd exposure resulted in a significant accumulation of Cd in adipose tissue and a decrease in both epididymal adipose tissue depot and adipocyte size. Cd exposure significantly decreased adipocyte gene1/ mesoderm-specific transcript, peroxisome proliferator-activated receptor γ2, and CCAAT/enhancer-binding protein α mRNA expression levels.

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Table 1 The influence of Cd exposure on metabolic parameters in laboratory studies (in a chronologic order). Object

Tissue

Cd exposure

Effect

Reference

In vivo Male Wistar rats

WAT

9.7 mg/l – 6 weeks

Ficková et al., 2003

MT-null mice

WAT

n.s. – 7 days

MT-null mice

WAT

0–0.75 mg/kg (s.c.) – 7 days

↔ Weigh gain ↑ Cd content in liver ↔ Adipocyte size ↓ Total insulin receptors number and density ↔ GLUT4 content ↓ Epididymal adipocyte size ↓ Adiponectin mRNA ↓ Leptin mRNA ↑ MCP-1 expression ↑ Macrophage infiltration ↓ WAT weight ↓ Adipocyte size ↓ Plasma leptin ↓ Leptin mRNA ↓ Resistin mRNA ↓ PPARγ2 mRNA ↓ C/EBPα mRNA ↑ MCP-1 expression ↑ Macrophage infiltration

In vitro Wistar rats

Adipocytes

0–5000.0 μM

↑ Lipogenesis ↔ 3-O-methylglucose uptake Cell line 3T3-L1 adipocytes 5–25 μM ↑ 2-Deoxyglucose uptake ↑ ROS ↑ GSH ↓ Adipocytes viability Wistar rats Adipocytes 5–5000 μM ↑ CO2 formation from glucose ↑ Lipogenesis Cell line 3 T3-L1 adipocytes 5, 10 μM ↑ Glucose uptake ↑ GLUT1 ↔ GLUT4 Sprague-Dawley rats Adipocytes 0–5 mM ↑ Glucose uptake ↑ GLUT1 ↑ GLUT4 Sprague-Dawley rats Adipocytes 0.01–10 mM ↓ Leptin secretion Sprague–Dawley rats Adipocytes 2 ml/kg b.w. for 4 days ↓ GLUT4 protein ↓ GLUT4 mRNA ↔ GLUT1 protein ↔ GLUT1 mRNA ↓ 3-O-methy-D-glucose uptake Cell line 3T3-L1 adipocytes 30 μM ↓ Adipocytes viability Slc:ICR mice Adipocytes 0–30 μmol Cd/kg b.w. – 6 h ↓ Gene 1/Mesoderm-specific transcript mRNA (0–20 μmol Cd/kg b.w., 3.5 times/week) – 2 weeks ↓ Peroxisome proliferator-activated receptor γ2 ↓ CCAAT/enhancer-binding protein α mRNA ↓ Adiponectin mRNA ↓ Resistin mRNA Cell line 3T3-L1 adipocytes 0.3–3 μM ↓ Glycerol-3-phosphate dehydrogenase (GPDH) ↓ Lipid accumulation ↓ C/EBPα mRNA ↓ PPARγ mRNA MT-null mice Adipocytes 0–100 μM (6–48 h) ↓ PPARγ2 mRNA ↓ Fatty acid synthase mRNA ↓ Acetyl CoA carboxylase α mRNA ↓ Hormone-sensitive lipase mRNA ↓ Adipose triglyceride lipase mRNA ↓ Perilipin 1 mRNA ↓ Resistin mRNA ↓ Adiponectin mRNA ↓ PAI-1 mRNA

Kawakami et al., 2012

Kawakami et al., 2013

Yamamoto et al., 1984 Kang et al., 1986

Yamamoto et al., 1986 Harrison et al., 1991

Lachaal et al., 1996a, 1996b

Levy et al., 2000 Han et al., 2003

Moon and Yoo, 2008 Kawakami et al., 2010

Lee et al., 2012

Kawakami et al., 2013

↑ – significant increase; ↓ – significant decrease; ↔ – no significant changes; n.s. – not specified.

A significant Cd-induced decrease in adiponectin and resistin expression was also observed (Kawakami et al., 2010). An in vitro study demonstrated that exposure to 0.3–3 μM CdCl2 resulted in a significant dosedependent decrease in lipid accumulation in differentiating 3T3-L1 cells on the stage of preadipocyte differentiation. It is also specified that Cd exposure significantly altered the expression of adipogenesis activators, CCAAT/enhancer-binding protein alpha (C/EBPα) and peroxisome proliferator-activator receptor gamma (PPARγ) (Lee et al., 2012).

Multiple studies demonstrated a significant effect of Cd on carbohydrate metabolism in adipocytes. In particular, an earlier study demonstrated a significant Cd-induced increase in CO2 formation from glucose in adipocytes (Yamamoto et al., 1986). Kang et al. revealed a 2.2- and 2.8-fold increase in 2-deoxyglucose uptake by 3 T3-L1 adipocytes in response to treatment with 10 and 25 μM of CdCl2 for 12 h. Moreover, the authors proposed that Cd-induced glucose uptake in adipocytes is related to altered Ca2+ signaling rather to insulin signaling

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(Kang et al., 1986). It is supposed that the observed increase in Cdinduced glucose uptake in 3T3-L1 adipocytes is mediated through modulation of GluT1 activity (Harrison et al., 1991). A later study also confirmed this observation, although being indicative of a simultaneous increase in GluT4 activity (Lachaal et al., 1996a, 1996b). At the same time, an earlier study demonstrated that adipocytes exposed to CdCl2 were characterized by increased rate of lipogenesis from glucose (Yamamoto et al., 1984). It has also been demonstrated that adipocytes obtained from rats subcutaneously exposed to CdCl2 (2 mg/kg – 4 days) were characterized by a significant dose-dependent decrease in GluT4 at both protein and mRNA levels, whereas neither GluT1 nor GluT2 were affected. It is also notable that GluT4 was selectively affected by Cd exposure only in adipose tissue but not in muscles. The observed effects were accompanied by decreased 3-O-methy-D-glucose uptake in insulin-stimulated adipocytes from Cd-exposed animals (Han et al., 2003). Therefore, the existing epidemiologic data do not clearly support the role of cadmium exposure in obesity, possibly for the biases affecting some of these human studies. However, laboratory studies show that Cd may alter adipose tissue physiology and induce an obesityassociated metabolic profile, features that may ultimately increase predisposition to diabetes and metabolic syndrome (Simmons et al., 2014). 4. Cadmium and type 2 diabetes mellitus 4.1. Human studies In contrast to obesity, the association between Cd exposure and diabetes mellitus type 2 (DM2) has been more extensively studied (Table 2). In particular, large cross-sectional studies showed a significant relationship between diabetes prevalence and indicators of Cd exposure. In particular, a detailed analysis of data from NHANES III (1988–1994) involving 8722 adults demonstrated that urinary Cd levels are associated with impaired fasting glucose and diabetes in a dosedependent manner even after adjustment for age, ethnicity, sex, and BMI (Schwartz et al., 2003). A cross-sectional SPECT-China study involving 5544 adults revealed a significant direct association (p b 0.01) between blood Cd levels and prediabetes in a model adjusted for age, gender, residence area, economic status, current smoker, hypertension, dyslipidemia, estimate glomerular filtration rate, blood lead concentrations, and BMI. However, no association (p = 0.347) between Cd and diabetes was detected (Nie et al., 2016). An examination of 4585 subjects who participated in the Malmö Diet and Cancer Study (1991–1994) revealed a significant association between blood Cd and glycated hemoglobin (HbA1c) levels in both men and women (p b 0.001), whereas no effect of Cd concentration on insulin and homeostatic model assessment insulin resistance (HOMA-IR) values was observed. Moreover, the investigators failed to detect any relationship between blood Cd levels and the incidence of diabetes. Taking into account a tight relationship between blood Cd and smoking, the authors have proposed that the observed findings can be explained by smoking status and erythrocyte turnover (Borné et al., 2014). A significant non-linear association between urinary Cd levels and prediabetes was also revealed. In particular, the OR for prediabetes were increased in the 3–5 quintiles of urinary Cd concentration, whereas after adjustment for various factors including age, BMI, smoking status, the association remained significant in the highest quintile (Wallia et al., 2014). Interestingly, the Cd accumulation in Langerhans islets of β-cells from the general US population tends to increase with age (Wong et al., 2015). It is also notable that the results of a case-cohort study revealed a significant association between higher urinary Cd levels and the incidence of gestational diabetes and adjustment for obesity did not affect the association (Romano et al., 2015). The level of Cd was found to be 25% (p b 0.001) higher in patients with DM2 and significantly correlated with FPG values (Akinloye et al., 2010). Moreover, a detailed multi-element analysis revealed a significant N3-fold increase in serum Cd levels in diabetic patients, being

accompanied by a nearly 3-fold decrease in its urinary concentrations (Flores et al., 2011). It has also been demonstrated that hair, blood, and urinary Cd levels were higher in diabetic patients irrespectively of the smoking status. In particular, in non-smoking and smoking people with diabetes the levels of Cd in hair, blood, and urine were 76 and 61%, 36 and 68%, and 46 and 48% higher than those in the respective control groups (Afridi et al., 2010). A later study also detected higher hair Cd levels in Iranian diabetic women (Tadayon et al., 2013). The studies involving persons occupationally or environmentally exposed to high Cd levels also provide additional support for the association between Cd exposure and DM2. In particular, the results of a 5year follow-up study in Cd-polluted area of Northwestern Thailand revealed a significant increase in the prevalence of diabetes in persons with prolonged Cd exposure (from 6.9% to 11.1%, p = 0.021), while no increase (p = 0.375) was detected in persons who reduced Cd exposure by giving up smoking and eating local rice (Swaddiwudhipong et al., 2012). A 19-year follow-up study in a polluted area in China also revealed a significant increase in blood (11 cases) and urinary glucose levels (8 cases) in exposed group, whereas only a single case with abnormal blood glucose was observed in the control group (Zhang et al., 2014). A recent study involving 535 persons from 13 Cd-contaminated villages demonstrated that Cd exposure was associated with the higher prevalence of diabetes (Tangvarasittichai et al., 2015). An earlier study demonstrated that females exposed to Cd from a polluted environment possess increased the risk of death from diabetes. However, the authors state that these could include deaths from Cd-induced nephropathy (Nakagawa et al., 1987). Interesting data were obtained during examination of Cd-exposed workers. It has been demonstrated that persons occupationally exposed to Cd from a smelter for N 10 and 20 years are characterized by elevated blood glucose levels and decreased serum insulin, respectively. In addition, blood and urinary Cd levels inversely correlated with serum insulin (Lei et al., 2006). A later study failed to reveal any significant association between urinary Cd levels and blood glucose. However, smelters with increasing urinary Cd level were characterized by lower insulin levels (Lei et al., 2007a). The results obtained from Health Effect Surveillance for Residents in Abandoned Metal Mines revealed an association between urinary cadmium levels and the prevalence of diabetes as well as blood glucose level in males, whereas the relations were not significant for blood Cd concentration and female sex (Son et al., 2015). A few studies have revealed no relationship between Cd exposure and DM2 or insulin resistance. Briefly, no association between urinary Cd levels and the incidence of diabetes in Cd-exposed population was detected in Mae Sot district, Tak province of Thailand (Swaddiwudhipong et al., 2010a) and Northwestern Thailand (Swaddiwudhipong et al., 2010b). Moreover, a recent systematic review of epidemiological data demonstrated that Cd is not significantly associated with DM2 (Kuo et al., 2013). Similarly, no association between blood Cd levels and the incidence of DM2 was revealed in KNHANES (2009–2010). Moreover, the level of Cd was not related to HOMA-IR, HOMA-β, and fasting insulin levels in regression models adjusted for age, sex, BMI, region, smoking, alcohol consumption and regular exercise (Moon, 2013). The results of the cross-sectional and prospective study revealed no significant relationship between the incidence of diabetes and impaired glucose tolerance and Cd levels at baseline. Moreover, no significant associations between baseline blood and urinary Cd levels with insulin production, blood glucose, HbA1c, or changes in HbA1c were detected (Barregard et al., 2013). No significant group difference in plasma Cd levels in controls and patients with diabetes, impaired fasting glucose, and impaired glucose tolerance was revealed. In addition, the study also failed to detect any association between plasma Cd and both blood glucose and HbA1c (Serdar et al., 2009). Correspondingly, the results obtained in Arizona demonstrated the absence of significant relationship between dietary Cd and the incidence of diabetes in both crude and adjusted logistic regression models (Kurzius-Spencer, 2013).

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Table 2 Summary of epidemiologic studies investigating the association between biomarkers of cadmium exposure and risk of diabetes or related metabolic abnormalities. Reference

Study design

Population/country

Schwartz et al., 2003

Cross-sectional NHANES III/US

Afridi et al., 2008

Cross-sectional Pakistan

Time frame

n

Cd exposure levels

Outcome

Risk estimate (95% CI)

1988–1994 8722 Urine (μg/g creatinine)

0–0.99 vs ≥2

↑ IFG ↑ DM2

OR = 2.05 (1.42–2.95) IFG OR = 1.45 (1.07–1.97) DM

2008

4.2 ± 1.25b 5.7 ± 1.3b 3.2 ± 0.9b 4.65 ± 0.79b 1.42 ± 0.3b 2.5 ± 0.26b b1.36 (T1) vs N2.89 (T3) ♂ b1.72 (T1) vs N3.65 (T3) ♀ b5 vs ≥15

Control DM2 Control DM2 Control DM2 ↔ DM2b ↑ DM2b

0.0071 ± 0.0014 0.0054 ± 0.0016 0.13 ± 0.48 0.04 ± 0.01 0.13 ± 0.12 0.32 ± 0.21 9.6 ± 1.7 (2005) 8.8 ± 1.6 (2010)

DM2 Control DM2 Control DM2 Control Reducing exposure: ↓ U-Cd ↑ U-β2-microglobulin ↑ U-protein ↑ Serum creatinine Continuing exposure: ↔ U-Cd ↑ DM2 ↑ hypertension ↑ U-β2-microglobulin ↑ U-protein ↑ Serum creatinine ↔ DM2 + IGT ↔ Insulin level ↔ Blood glucose ↔ HbA1c

826

Cd biomarker

Blood (μg/l) Urine (μg/l) Hair (μg/g)

Swaddiwudhipong et al., 2010b

Cross-sectional Thailand

2009

5273 Urine (μg/g creatinine)

Swaddiwudhipong et al., 2010a Akinloye et al., 2010

Cross-sectional Thailand

2005

795

Cross-sectional Nigeria

2010

90

Flores et al., 2011

Cross-sectional Mexico

2010

76

Swaddiwudhipong et al., 2012

5-year follow-up

2005–2010 484

Thailand

Urine (μg/g creatinine) Blood (μmol/l) Serum (μg/dl) Urine (μg/dl)

Urine (μg/g creatinine)

9.3 ± 1.6 (2005) 8.9 ± 1.7 (2005)

Barregard et al., 2013

Cross-sectional Sweden

2001–2003 2595 Blood (μg/l)

0.34 (0.13–1.92) vs 0.34 (0.17–0.61)

Urine (μg/g creatinine)

0.36 (0.14–1.14) vs 0.36 (0.16–0.92)

Hair (μg/dg)

~0.017a ~0.05a 0.55 ± 1.01 (Q1) vs 2.11 ± 1.01 (Q4)

Prospective cohort

100

↔/↑ DM2

DM2 Control ↔ DM2 ↔ HOMA-IR ↔ HOMA-β ↔ Fasting insulin ↑ HbA1c ↔ DM2 incidence

Tadayon et al., 2013

Cross-sectional Iran

2013

Moon, 2014

Cross-sectional KNHANES/Korea

2009–2010 3184 Blood (μg/l)

Borné et al., 2014

Prospective cohort

Malmo Diet and Cancer Study/Sweden

1991–1994 4585 Blood (μg/l)

Wallia et al., 2014

Cross sectional

NHANES/US

Son et al., 2015

Cross-sectional HESRAM Study/Korea

2005–2010 2398 Urine (μg/g creatinine) 2008–2011 719 Urine (μg/g creatinine)

0.01–0.15 (Q1) vs 0.51–5.07 (Q4) ♂ 0.02–0.18 (Q1) vs 0.50–4.83 (Q4) ♀ 0.014–0.183 (Qi1) vs 0.656–3.74 (Qi5) ≤1 (T1) vs ≥ 2 (T3) ♂ ≤1 (T1) vs ≥ 3 (T3) ♀

Nie et al., 2016

Cross-sectional SPECT-China study

2016

≤0.80 (T1) vs ≥2.95 (T3)

↑ FPG ↑ Prediabetes ↔ DM2

Tangvarasittichai et al., 2015

Cross-sectional Thailand

2010–2011 534

9.76 ± 5.58 (cases) 1.14 ± 1.18 (controls)

↔ Glucose ↑ DM2

5544 Blood (μg/l)

Urine (μg/g creatinine)

↑ Prediabetes risk ↑ DM2 ↔ DM2

OR = 1.007 (0.932–1.088) ♂ OR = 1.022 (0.981–1.065) ♀ OR = 1.02 (0.99–1.06)

OR = 1.2 (0.5–2.6) cross OR = 2.2 (0.9–6.1) cohort OR = 1.1 (0.6–2.2) cross OR = 1.2 (0.5–2.6) cohort

OR = 0.898 (0.633–1.275)

HR = 1.11 (0.82–1.49) ♂ HR = 0.90 (0.59–1.38) ♀ OR = 1.67 (1.12, 2.47) OR = 1.81(1.05–3.12) OR = 1.39 (0.52–3.72) OR = 1.37 (1.14–1.63) pre OR = 1.13 (0.88–1.46) DM OR = 3.02 (1.23–7.38)

↑ – significant increase; ↓ – significant decrease; ↔ – no significant changes. T – tertile; Q – quartile; Qi – quintile. OR – odds ratio; HR – hazard ratio. Abbreviations: DM2 - diabetes mellitus type 2; HOMA-IR - homeostatic model assessment insulin resistance; HOMA-β - homeostatic model assessment β-cell function; U-Cd – urinary Cd; IGT - impaired glucose tolerance; FPG - fasting plasma glucose; HbA1c - glycated hemoglobin. a Only figure is provided without exact values. b Only non-smokers.

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Fig. 1. Meta-analysis of the odds ratio (OR), with 95% CI for pre-diabetes prevalence (A), diabetes prevalence (B), and diabetes incidence (C).

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Table 3 The influence of Cd exposure on carbohydrate metabolism in laboratory models. Object

Sample

Cd exposure

Effect

Reference

In vivo Male adrenalectomized mice

Blood

2–6 mg/kg b.w. (Cd acetate)

↑ Blood glucose, dose-dependent

Diabetic rats

Blood

Female alloxan-diabetic rats

Female rats

Pancreas Liver Blood Spleen Kidneys Blood

Male Sprague-Dawley rats

Blood, liver

Male Sprague-Dawley rats

Blood Kidney Liver

Female rats

Blood

Diabetic rats

Blood

Male Sprague-Dawley rats Female Wistar rats

Blood Pancreas

Female ovariectomized cynomolgus monkeys

Pancreas

Male Wistar rats

Blood

Sprague-Dawley rats

Pancreas Blood Urine

Sprague-Dawley rats

Blood Pancreas

Wistar rats

Blood, liver, muscle, adipose and cardiovascular tissue

C57BL/6 male mice

Liver, fat, blood, feces

0.25–0.50 mg/kg b.w. (20 doses) (Cd ↔ Plasma glucose acetate) ↔ Plasma insulin ↔ Body weight ↑ Glucose oxidation 15 μCi of 109Cd, 0.0625 mg Cd acetate ↓ Liver Cd uptake per dose, single-shot ↓ Pancreas Cd level ↑ Blood Cd levels ↑ Kidney Cd levels ↔ Spleen Cd levels 0.25–0.50 mg/kg b.w. (70 doses) (Cd ↓ Insulin secretion acetate) ↓ Body weight ↑ Urine glucose ↔ Plasma glucose 1 mg/kg b.w. twice daily for 7 days ↓ Insulin release ↑ Serum glucose ↑ Hepatic cAMP ↑ Gluconeogenic enzymes activity in liver ↓ Liver glycogen ↓ Body weight gain 0–200 ppm for 30 days (CdCl2) ↑ Serum glucose ↑ Serum protein ↑ Gluconeogenic enzymes activity in liver and kidney 200 μg/g of diet for 40 weeks ↑ Serum GPT ↓ Serum glucose ↑ Serum insulin 2 mg/kg i.p. for 21 days ↑ Blood Cd levels ↑ Blood glucose ↑ Brain dopamine ↑ Brain 5-hydroxytryptamine 0.84 mg/kg b.w. ↑ Blood glucose 0.49 mg/kg/day for 20 days ↑ Pancreas degeneration, necrosis, and 50 mg STZ/kg b.w. once degranulation ↑ Serum glucose ↓ Serum insulin ↑ Pancreas changes in Cd + STZ group ↓ Islet number and vacuolation of the islet 1.0–2.5-mg/kg group (CdCl2) cells ↔ Exocrine acinar cells ↓ Insulin-positive areas in the islets ↔ Glucagon-positive areas ↑ Blood glucose ↓ Blood insulin ↑ Cd levels in liver, kidney and pancreas ↑ MT levels in liver, kidney and pancreas ↓ Plasma IGF-I and IGFBP-3 levels 50 mg/l (CdCl2) ↔ GH 0.5–2.0 mg/kg b.w. ↑ Pancreas Cd ↑ Serum glucose ↔ Serum insulin ↔ Urine NAG ↑ Insulin, MT-I and MT-II mRNA 0.6 mg/kg 5 days/week, for 12 weeks ↑ Serum glucose ↑ HbA1С levels (CdCl2) ↓ Serum insulin ↑ Pancreatic Cd ↔ Renal dysfunction ↑ Disruption of pancreatic cell morphology ↑ Blood glucose 32.5 ppm (CdCl2) ↑ Fasting insulin ↑ Proatherogenic changes ↑ HOMA-IR ↓ Insulin sensitivity in muscle and liver ↑ Insulin resistance in the liver, AT and CV system ↑ Hepatic GluT2 1.0–10.0 mg/l for 10 weeks (CdCl2) ↑ Chrebp ↑ Glucokinase mRNA ↑ Pyruvate kinase mRNA ↑ Serum glucose ↑ Hepatic TG

Ghafghazi and Mennear, 1973 Ithakissios et al., 1974

Ithakissios et al., 1974

Ithakissios et al., 1975

Merali and Singhal, 1976, 1980

Chapatwala et al., 1980

Nakamura et al., 1983 Chandra et al., 1985

Bell et al., 1990 Kanter et al., 2003

Kurata et al., 2003

Turgut et al., 2005 Lei et al., 2007b

Edwards and Prozialeck, 2009

Treviño et al., 2015

Zhang et al., 2015

(continued on next page)

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Table 3 (continued) Object

Sample

Cd exposure

Effect

Reference

↑ Serum FFA, TG, and LPS levels ↓ Gut microbiome ↑ TNFa, IL-1β, and IL-6 mRNA In vitro Male Sprague-Dawley rats

Perfused pancreas

1–5 mM Cd2+

Cd-exposed male Swiss mice

Pancreatic islets cells

2.0 mg Cd/kg bw 1 μM Cd2+ as Cd acetate

Cd-exposed neonatal male Sprague-Dawley rats Adult obese-hyperglycemic mice

Pancreatic islets cells Pancreatic islets cells

0.1 and 1.0 μg CdCl2/g daily for 45 days 5–160 μM Cd2+

Adult obese-hyperglycemic mice

Pancreatic islets cells

5 μM Cd2+

Mice

Kidney cortical tubule cells

0–0.6 μM for 24 h

Male Sprague-Dawley rats

Hepatocytes

0–12.5 μM for 2 h (Cd acetate)

Sprague-Dawley rats

Adipocytes

0.1–5 mM CdSO4 for 30 min

Human

β-Cell line MIN6

0.1–1.0 μmol/l for 72 h

Rats

RIN-m5F pancreatic β-cell

3–10 μM for 24 h (CdCl2)

↓ Glucose, potassium ions, and tolbutamide-stimulated insulin secretion ↔ Glucose-stimulated insulin secretion in Cd-pretreated mice ↑ Metallothionein level ↓ Glucose-stimulated insulin secretion 2+

↑ Basal insulin secretion by 5 μM Cd ↔ Basal insulin secretion by 160 μM Cd2+ ↓ Glucose-stimulated insulin secretion by 160 μM Cd2+ ↓ Glucose oxidation above 10 μM Cd2+ ↑ Cd2+ uptake of by the activation of voltage-dependent Ca2+ channels ↓ IP3-induced Ca2+ release ↑ Insulin release ↔ Independent of cytoplasmic Ca2+ levels ↓ Uptake of alpha-methylglucoside ↔ Amino acid analogue alpha-(methylamino)isobutyric acid uptake ↔ Lactate dehydrogenase activity ↔ Na+ and K+ concentrations ↓ Cell viability ↓ Glucose output ↓ GSH level ↑ 3OMG flux ↑ GluT4 and GluT1 ↑ Metallothionein expression ↓ Glucose-stimulated insulin secretion ↓ GSH level ↑ GCLM and HMOX1 mRNA ↓ Cell viability ↑ Intracellular ROS generation ↑ Intracellular MDA ↑ Cytosolic cytochrome c release ↓ Insulin secretion ↑ Phosphorylations of JNK, ERK1/2, and MAPK ↓ Bcl-2 expression ↑ p53 expression ↑ PARP cleavage ↑ Caspase cascades

Ghafghazi and Mennear, 1973 Yau and Mennear, 1977 Merali and Singhal, 1980 Nilsson et al., 1986

Nilsson et al., 1987

Blumenthal et al., 1990

Bell et al., 1991

Lachaal et al., 1996a, 1996b El Muayed et al., 2012

Chang et al., 2013

↑ – significant increase; ↓ – significant decrease; ↔ – no significant changes; abbreviations: Chrebp – carbohydrate regulatory element binding protein; IGF-I - insulin-like growth factor I; IGFBP-3 - insulin-like growth factor-binding protein 3; GH - growth hormone; NAG - N-acetyl-beta-glucosaminidase; IP3 - inositol 1,4,5-trisphosphate; JNK - c-jun N-terminal kinases; ERK1/2 - extracellular signal-regulated kinases 1/2; MAPK - p38-mitogen-activated protein kinase; PARP - poly (ADP-ribose) polymerase; 3OMG - 3-O-methyl-D-glucose.

We performed a meta-analysis of retrieved observational studies assessing the risk of prevalence and incidence of diabetes and prediabetes, comparing the higher versus the lowest exposure categories of cadmium intake and using a methodology already specified in detail (Vinceti et al., 2016). The extracted data for meta-analysis included study design (cross-sectional or cohort), number, sex and country of participants, type of cadmium specimen (blood or urine), the covariates adjusted for in the multivariable analysis and eventually the odds ratios (OR) estimates and their 95% CI for the most adjusted model reported. We used random-effect models to account for heterogeneity (I2) in study-specific results. We performed stratified analysis according to diabetes or prediabetes prevalence and incidence, type of sample and sex of participants. All but one (Barregard et al., 2013) studies adjusted for sex and age, and all studies but two adjusted for smoking status, but they performed stratified analysis for smokers and never smokers (Schwartz et al., 2003; Swaddiwudhipong et al., 2010b). Two studies were performed in Europe (Sweden), three in America (US and Mexico), and six in Asia. Summary ORs for prevalence of prediabetes and diabetes were 1.60 (95% CI 1.25 to 2.06) and 1.04 (95% CI 0.99 to 1.10), respectively, and risk of diabetes incidence was 1.38 (95% CI 1.12 to 1.71) (Fig. 1).

Stratified analysis according to type of sample (blood or urine) and sex of participants are reported in Table 3. Our results showed higher OR for studies using urine for cadmium exposure assessment in both prediabetes prevalence and diabetes incidence, but not in diabetes prevalence. According to sex, a slight higher risk of prevalent diabetes was found in men though less precise than for studies in females, while for studies on diabetes incidence women showed higher risk due to cadmium exposure, however only one study was carried out in men. 4.2. Experimental data An adverse effect of Cd exposure on carbohydrate metabolism and its regulation in experimental models was revealed N40 years ago (Table 4). Ghafghazi and Mennear (1973) demonstrated that intraperitoneal administration of single doses of cadmium acetate to mice resulted in a significant dose-dependent increase in blood glucose, being maximal in 2 h after Cd treatment (Ghafghazi and Mennear, 1973). Ithakissios and coauthors have demonstrated altered insulin secretion and glucose handling in normal (Ithakissios et al., 1975) and diabetic Cd-exposed rats (Ithakissios et al., 1974). It has also been demonstrated

A.A. Tinkov et al. / Science of the Total Environment 601–602 (2017) 741–755 Table 4 Summary odds ratio (OR) with 95% confidence interval (CI) and heterogeneity (I2) of the meta-analysis of studies on the risk of prediabetes or diabetes according to cadmium exposure. N studies

OR

(95% CI)

I2 (%)

3

1.60

(1.25 to 2.06)

50.9

2 1

1.87 1.37

(1.43 to 2.44) (1.15 to 1.64)

0.0 –

9

1.04

(0.99 to 1.10)

40.1

6 3

1.05 1.05

(0.98 to 1.11) (0.86 to 1.28)

0.0 54.6

5 2 4

1.15 1.27 1.02

(0.94 to 1.40) (0.72 to 2.22) (0.98 to 1.07)

65.8 77.1 0.0

20,555

7

1.38

(1.12 to 1.71)

51.4

10,168 10,387

3 4

1.79 1.21

(1.39 to 2.31) (0.96 to 1.53)

0.0 42.8

13,059 1831 3267

2 1 3

1.62 0.90 1.18

(1.10 to 2.39) (0.59 to 1.38) (0.90 to 1.55)

73.5 – 0.0

Participants Prediabetes prevalence Overall 15,457 Type of sample Urine 9913 Blood 5544 Diabetes prevalence 25,297 Overalla Type of sample Urine 15,424 Blood 9296 Sex-stratified All 18,160 Males 2859 Females 4269 Diabetes incidence Overallb Type of sample Urine Blood Sex-stratified All Males Females

a In sensitivity analysis the summary OR for prevalence diabetes did not change after alternatively exclusion of results of one study (Barregard et al., 2013) that reported estimates for both urine and blood specimen. b In sensitivity analysis the summary OR for diabetes incidence was 1.35 (1.12 to 1.71) removing blood specimen and 1.40 (1.11 to 1.75) removing urine specimen.

that diabetes significantly affected Cd uptake and distribution. In particular, blood Cd levels in diabetic Cd-exposed animals were significantly higher in comparison to non-diabetic animals. Moreover, liver and spleen Cd content was higher in diabetic rats in 24 h from exposure, whereas pancreatic Cd content in this period of time was lower than the non-diabetic values. At the same time, the differences were not significant in 240 h except liver, where it became lower (Ithakissios et al., 1974). It has been also demonstrated that Cd-exposed alloxaninduced diabetic rats are characterized by significantly elevated blood

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Cd and glucose levels as compared to both Cd-exposed and diabetic controls, being indicative of interactive effect of Cd and diabetes on hyperglycemia (Chandra et al., 1985). Intraperitoneal injection of cadmium acetate (0.84 mg/kg weight) has been shown to cause a significant elevation of blood glucose in experimental animals in 30 min after injection (Bell et al., 1990). Administration of 0, 50, 100, 150 and 200 ppm CdCl2 for 30 days resulted in a significant dose-dependent elevation of blood glucose levels. In particular, administration of 200 ppm of dietary Cd caused a significant nearly 3-fold increase in serum glucose as compared to the control levels. A dose-dependent Cd-induced activation of glucogenic enzymes (pyruvate carboxylase, phosphoenol pyruvate carboxykinase, fructose-1, 6diphosphatase and glucose-6-phosphatase) was observed both in liver and kidneys (Chapatwala et al., 1980). A detailed study by Treviño and coauthors demonstrated that chronic Cd treatment (32.5 ppm Cd as CdCl2) induced insulin resistance in rats. In particular, the levels of fasting glucose and insulin were significantly increased in comparison to the control values after 2 months of treatment whereas HOMA-IR and other indices of insulin sensitivity were affected after the first month of exposure. Moreover, a significant increase in adipose tissue dysfunction index, cardiovascular resistance index, as well as hepatic and muscle insulin resistance was observed in Cd-treated animals (Treviño et al., 2015). The results of an excellent study by Zhang et al. (2015) demonstrated that Cd exposure (10 mg/l) may involve various mechanisms of insulin resistance development. Briefly, the authors have demonstrated that Cd exposure results in significant increase in hepatic GluT2, carbohydrate regulatory element binding protein (Chrebp), glucokinase, and pyruvate kinase mRNA. In parallel, activation of lipogenic proteins, was also detected. Cd exposure resulted in a significant increase in serum glucose and free fatty acids. Cd treatment significantly altered gut microbiome, increased the level of LPS in serum and transcriptional status of LPS target genes, finally leading to induction of inflammatory response through elevation of TNFa, IL-1β, and IL-6 mRNA (Zhang et al., 2015). These findings are of great importance for the understanding of the link between Cd exposure, diabetes and obesity. In particular, it has been demonstrated that elevated FFA levels induce insulin resistance (Boden et al., 2005), whereas LPS is associated with insulin resistance and obesity (Cani et al., 2007). In addition, oral administration of 50 mg/l CdCl2 with drinking water for 1 month in young male rats resulted in a

Fig. 2. A simplified scheme of the potential mechanisms of the impact of Cd on adipose tissue physiology and their potential contribution to insulin resistance.

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significant decrease in plasma insulin-like growth factor 1 and insulin-like growth factor-binding protein 3 levels (Turgut et al., 2005) that are also known to be altered in diabetes mellitus (Mohamed-Ali and Pinkney, 2002). Ghafghazi and Mennear demonstrated that Cd perfusion of isolated rat pancreas altered insulin secretory response to glucose, potassium ions, and tolbutamide (Ghafghazi and Mennear, 1975). Oral administration of Cd resulted in a significant accumulation of the metal in pancreas and a significant decrease in serum insulin levels (Lei et al., 2005a). However, gene expression of insulin in animals was not affected after 90 days of treatment with Cd-containing water (Lei et al., 2005b). Later data obtained by the authors demonstrated that subcutaneous injection of cadmium resulted in increased pancreatic Cd content, glucose intolerance, and decreased gene expression of insulin, whereas serum insulin level was not changed significantly in comparison to the control values (Lei et al., 2007a, 2007b). In general, these findings are in agreement with the earlier observation of the association between 7-day Cd treatment and impaired glucose tolerance, elevated blood glucose, decreased insulin production, decreased liver glycogen and higher activity of hepatic gluconeogenesis (Merali and Singhal, 1976, 1980). Multiple studies demonstrated the effect of cadmium on pancreatic structure. In particular, chronic Cd exposure in mice caused alteration of the endocrine part of the pancreas with decreased number of secretory granules, whereas the exocrine part was characterized by acidophil and fatty degeneration (Jiang et al., 1998). Subcutaneous injection of CdCl2 during pregnancy resulted in degeneration, necrosis, and weak degranulation of pancreatic β-cells of pregnant rats. It is notable that Cd exposure in diabetic animals (streptozotocin-induced) was associated with more severe changes in pancreatic histology (Kanter et al., 2003). Cd injections in ovariectomized cynomolgus monkeys for 13– 15 months caused a significant accumulation of Cd in pancreas, being associated with islet atrophy and β-cell vacuolization. Further examination revealed a significant decrease in insulin-positive areas. The observed changes were detected only in the endocrine part of the pancreas, whereas no significant alteration was detected in the exocrine part. The morphological changes were also associated with decreased blood insulin levels and hyperglycemia (Kurata et al., 2003). At the same time, the results of the earlier study demonstrated that prolonged dietary Cd (200 μg/g of diet) consumption resulted in a significant decrease in blood glucose levels and a N 2-fold elevation of serum immunoreactive insulin concentration at the 40th week of the experiment (Nakamura et al., 1983). In vitro studies using cell cultures or cells from Cd-exposed animals demonstrated that pancreatic β-cells are the targets for Cd toxicity and the effect is mediated through various mechanisms. In particular, the earlier studies have demonstrated that incubation of isolated murine pancreatic islets with Cd is accompanied with a decrease in glucoseinduced insulin secretion, whereas metallothionein was shown to have a protective effect (Yau and Mennear, 1977). Similarly, pancreatic β-cells isolated from Cd-exposed animals were characterized by impaired insulin secretion in the presence of high glucose levels (1.5 and 3.0 mg/ml) in comparison to the control values (Merali and Singhal, 1980). Incubation of human β-cell line MIN6 with increasing CdCl2 concentrations resulted in a significant dose- and time-dependent accumulation of cadmium, being associated with induction of metallothionein expression and inhibition of glucose-stimulated insulin secretion (El Muayed et al., 2012). A detailed study demonstrated that Cd accumulation in pancreatic β-cells is stimulated by glucose and potassium but is reduced by Ca2+ (20 mM in the medium). It has been also demonstrated that 5 μM Cd2 + stimulated basal insulin secretion. Higher levels of cadmium (160 μM) did not affect basal insulin secretion but significantly decreased glucose-induced insulin release. The authors proposed that Ca2+ transport in β-cells can be at least partially mediated by voltagedependent Ca2 + channels (Nilsson et al., 1986). The authors have

further demonstrated that Cd treatment resulted in a significant 3-fold increase in glucose-induced insulin release in β-cells isolated from obese hyperglycemic mice. A detailed study with voltage-activated Ca2+ channel blocker demonstrated that this effect was independent of alteration of cytoplasmic Ca2+ levels (Nilsson et al., 1987). Cd exposure resulted in decreased viability in pancreatic β-cellderived RIN-m5F cells, elevated ROS production, mitochondrial dysfunction, decreased Bcl-2 and increased p53 expression, poly (ADP-ribose) polymerase (PARP) cleavage, and activation of caspase cascades. Cd treatment also increased phosphorylation of c-jun N-terminal kinases (JNK), ERK1/2, and p38 MAPK. It is notable, that all of the observed effects of Cd exposure were reversed by N-acetylcysteine pretreatment, being indicative of the key role of oxidative stress in Cd toxicity in pancreatic β-cells (Chang et al., 2013). In parallel with pancreatic β-cells and adipocytes, Cd exposure also affects glucose transport in other tissues. In particular, incubation of rat hepatocytes with increasing doses of cadmium acetate (0–12.5 μM) resulted in a significant dose-dependent decrease in glucose output, being N2-fold lower at the highest Cd concentration as compared to the control medium (0 μM Cd) (Bell et al., 1991). It has been also demonstrated that 0–0.6 μM Cd2+ exposure for 24 h resulted in a significant dose-dependent inhibition of glucose uptake in primary cultures of mouse cortical tubule cells (Blumenthal et al., 1990). It is also notable that that cadmium affects the substrate binding activity of GluT1, being a glucose transporter in erythrocytes (Lachaal et al., 1996a, 1996b). Generally, the existing clinical and experimental data demonstrate that the amount of Cd exposure associated with diabetes and insulin resistance may also be associated with proinflammatory effects of Cd ion. Moreover, direct effect of Cd on pancreatic β-cells is associated with cellular degeneration and decreased viability, as well as impaired insulin secretion in response to metabolic stimuli (Edwards and Prozialeck, 2009). 5. Conclusion Therefore, despite some inconsistencies, the existing human and experimental data demonstrate that Cd plays a significant role in the etiology of diabetes and insulin resistance, even at moderate to low levels of exposure. Correspondingly, the results of our meta-analysis findings showed an elevated risk of diabetes incidence in subjects in the highest versus the lowest category of cadmium exposure. At the same time, the evidence supporting a role of Cd in inducing obesity is far less clear and consistent. However, there is evidence showing that Cd adversely affects adipose tissue physiology, resulting in impaired adipogenesis, altered lipid and carbohydrate metabolism in adipocytes, as well as in adipose tissue endocrine dysfunction. Overall, the existing data demonstrate that Cd-induced changes of adipose tissue physiology even without the presence of clinical obesity (increased adipose tissue mass) may at least partially predispose to insulin resistance and subsequent diabetes mellitus type 2, that seem to be characteristic for chronic Cd exposure (Fig. 2). Intimate biological mechanisms linking Cd exposure with obesity and diabetes are still to be investigated. Conflict of interest The authors declare no conflict of interest. References Adnan, J.A., Azhar, S.S., Hasni, J.M., Ahmad, J.S., 2012. Urinary cadmium concentration and its risk factors among adults in Tanjung Karang, Selangor. Am. Euras. J. Toxicol. Sci. 4, 80–88. Afridi, H.I., Kazi, T.G., Kazi, N., Jamali, M.K., Arain, M.B., Jalbani, N., Sarfraz, R.A., 2008. Evaluation of status of toxic metals in biological samples of diabetes mellitus patients. Diabetes Res. Clin. Pract. 80 (2), 280–288. Afridi, H.I., Kazi, T.G., Kazi, N.G., et al., 2010. Evaluation of cadmium, lead, nickel and zinc status in biological samples of smokers and nonsmokers hypertensive patients. J. Hum. Hypertens. 24 (1), 34–43.

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