Association between serum zinc and later development of metabolic syndrome in middle aged and older men: The Kuopio Ischaemic Heart Disease Risk Factor Study

Zinc and aging: a narrative review of the effects on hematopoiesis and its link with diseases

There has been a global increase in the older population in recent decades and, as age advances, complex metabolic and epigenetic changes occur in the organism, and these may trigger some health complications commonly found among this population. Additionally, several changes occur in older people that can reduce the dietary intake or the process of nutrient absorption. In this way, tissues with high nutrient requirements are more affected. Hematopoiesis is the process of formation, development, and maturation of blood cells and is a process with a high turnover. This high demand makes the integrity of the hematopoietic process susceptible to various factors that impair physiological function, such as aging and micronutrient bioavailability. Among these micronutrients, Zinc is considered an important micronutrient, playing diverse roles across various tissues and cell types. Some of the alterations in hematopoiesis that appear as a consequence of aging and due to insufficient micronutrient intake are well described in the literature; however, not much is known about how zinc deficiency contributes towards the development of diseases seen in aging. Considering the importance of zinc to act on several biological processes, this narrative review discusses several studies related to the physiological requirements, deficiency, or excess of zinc, including studies in experimental models and humans, and aimed to shed light on the relationship between zinc and the regulation of hematopoietic tissue, exploring possible links between this mineral with common disorders that appear during aging.

Association Between Circulating Zinc Levels and Risk Factors of Metabolic Syndrome: Insights from a Bi-directional Mendelian Randomization Analysis and Cross-Sectional Study

Previous studies on the relationship between zinc and metabolic syndrome (MetS) have yielded inconsistent results. This comprehensive study aimed to elaborately explore the impact of zinc on MetS risk factors. The bi-directional Mendelian randomization (MR) analyses were performed to estimate the causal relationship between zinc and MetS risk factors. Additionally, a retrospective cross-sectional study incorporated 4389 subjects to provide a broader perspective in conjunction with the MR analyses. In the MR analyses, genetically instrumented zinc was positively associated with five of the MetS components in Europeans, including BMI, FBG, HbA1c, TC, and LDL-c (β (95%CI) = 0.023 (0.019-0.027), 0.019 (0.013-0.025), 0.041 (0.022-0.060), 0.027 (0.013-0.042), and 0.018 (0.010-0.026), respectively). In the cross-sectional study, higher concentration of zinc was strongly associated with increased BMI, LDL-c, and UA (β (95%CI) = 0.040 (0.010-0.085), 0.026 (0.018-0.035), and 1.529 (0.614-2.445), respectively). Moreover, these unfavorable associations were more obvious in women compared to men, with a borderline significant interaction effect for BMI (P=0.051). Our study showed that higher blood concentration of zinc, an essential trace element, was associated with unfavorable changes of the component metabolic risk factors of MetS, especially with BMI and LDL-c. Notably, these associations seemed to be more pronounced in women rather than in men. Further studies are warranted to elucidate the role of zinc status in the underlying mechanisms of MetS.

Associations between plasma metal/metalloid mixtures and the risk of central obesity: A prospective cohort study of Chinese adults

Central obesity has increased rapidly over the past decade and posed a substantial disease burden worldwide. Exposure to metals/metalloids has been acknowledged to be involved in the development of central obesity through regulation of cortisol, insulin resistance, and glucocorticoid receptor reduction. Despite the importance, it is lack of prospective study which comprehensively evaluate the relations between multiple metals exposure and central obesity. We explored the prospective associations of plasma metal concentrations with central obesity in a prospective study of the Dongfeng-Tongji cohort. The present study included 2127 participants with a 6.87-year mean follow-up duration. We measured 23 plasma metal/metalloid concentrations at baseline. The associations between metals and incident central obesity were examined utilizing the Cox proportional hazard regression in single and multiple metals models. Additionally, we applied elastic net (ENET), Bayesian kernel machine regression (BKMR), plasma metal score (PMS), and quantile-based g-computation (Qgcomp) models to explore the joint associations of metal mixtures with central obesity. After adjusting potential confounders, we found significant associations of plasma manganese (Mn) and thallium (Tl) concentrations with a higher risk of central obesity, whereas plasma rubidium (Rb) concentration was associated with a lower risk of central obesity both in single and multiple metals models (all FDR <0.05). The ENET and Qqcomp models verified similar metals (Mn, Rb, and Tl) as important predictors for central obesity. The results of both BKMR model and PMS suggested cumulative exposure to metal mixtures was associated with a higher risk of central obesity. Our findings suggested that co-exposure to metals was associated with a higher risk of central obesity. This study expands our knowledge that the management of metals/metalloids exposure may be beneficial for the prevention of new-onset central obesity, which may subsequently alleviate the disease burden of late-life health outcomes.

Recent advances in the application of ionomics in metabolic diseases

Trace elements and minerals play a significant role in human health and diseases. In recent years, ionomics has been rapidly and widely applied to explore the distribution, regulation, and crosstalk of different elements in various physiological and pathological processes. On the basis of multi-elemental analytical techniques and bioinformatics methods, it is possible to elucidate the relationship between the metabolism and homeostasis of diverse elements and common diseases. The current review aims to provide an overview of recent advances in the application of ionomics in metabolic disease research. We mainly focuses on the studies about ionomic or multi-elemental profiling of different biological samples for several major types of metabolic diseases, such as diabetes mellitus, obesity, and metabolic syndrome, which reveal distinct and dynamic patterns of ion contents and their potential benefits in the detection and prognosis of these illnesses. Accumulation of copper, selenium, and environmental toxic metals as well as deficiency of zinc and magnesium appear to be the most significant risk factors for the majority of metabolic diseases, suggesting that imbalance of these elements may be involved in the pathogenesis of these diseases. Moreover, each type of metabolic diseases has shown a relatively unique distribution of ions in biofluids and hair/nails from patients, which might serve as potential indicators for the respective disease. Overall, ionomics not only improves our understanding of the association between elemental dyshomeostasis and the development of metabolic disease but also assists in the identification of new potential diagnostic and prognostic markers in translational medicine.

Strategy for sodium-salt substitution: On the relationship between hypertension and dietary intake of cations

Chronic diseases, especially cardiovascular diseases (CVD), have become one of the main causes affecting human health. Hypertension is a prominent representative of CVD. The formation and development of hypertension is closely related to people's daily diet. A large number of studies have shown that excessive intake of salt (NaCl) could increase the risk of hypertension. In recent years, more and more investigations have focused on other cations that may be contained in edible salt, exploring whether they have an effect on hypertension and the underlying mechanism. This article focuses on the relationship between four metal elements (potassium, calcium, magnesium, and zinc) and hypertension, by discussing the main metabolic pathway, the impact of diet intake on blood pressure, and especially the regulation mechanisms on blood pressure in detail. At the same time, some opinions and suggestions are put forward, combined with the current hot topics "salt reduction" and "salt substitution".

Gene-environment interaction analysis of redox-related metals and genetic variants with plasma metabolic patterns in a general population from Spain: The Hortega Study

Background

Limited studies have evaluated the joint influence of redox-related metals and genetic variation on metabolic pathways. We analyzed the association of 11 metals with metabolic patterns, and the interacting role of candidate genetic variants, in 1145 participants from the Hortega Study, a population-based sample from Spain.

Methods

Urine antimony (Sb), arsenic, barium (Ba), cadmium (Cd), chromium (Cr), cobalt (Co), molybdenum (Mo) and vanadium (V), and plasma copper (Cu), selenium (Se) and zinc (Zn) were measured by ICP-MS and AAS, respectively. We summarized 54 plasma metabolites, measured with targeted NMR, by estimating metabolic principal components (mPC). Redox-related SNPs (N = 291) were measured by oligo-ligation assay.

Results

In our study, the association with metabolic principal component (mPC) 1 (reflecting non-essential and essential amino acids, including branched chain, and bacterial co-metabolism versus fatty acids and VLDL subclasses) was positive for Se and Zn, but inverse for Cu, arsenobetaine-corrected arsenic (As) and Sb. The association with mPC2 (reflecting essential amino acids, including aromatic, and bacterial co-metabolism) was inverse for Se, Zn and Cd. The association with mPC3 (reflecting LDL subclasses) was positive for Cu, Se and Zn, but inverse for Co. The association for mPC4 (reflecting HDL subclasses) was positive for Sb, but inverse for plasma Zn. These associations were mainly driven by Cu and Sb for mPC1; Se, Zn and Cd for mPC2; Co, Se and Zn for mPC3; and Zn for mPC4. The most SNP-metal interacting genes were NOX1, GSR, GCLC, AGT and REN. Co and Zn showed the highest number of interactions with genetic variants associated to enriched endocrine, cardiovascular and neurological pathways.

Conclusions

Exposures to Co, Cu, Se, Zn, As, Cd and Sb were associated with several metabolic patterns involved in chronic disease. Carriers of redox-related variants may have differential susceptibility to metabolic alterations associated to excessive exposure to metals.

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In a population-based sample, cobalt, copper, selenium, zinc, arsenic, cadmium and antimony exposures were related to some metabolic patterns.

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Carriers of redox-related variants displayed differential susceptibility to metabolic alterations associated to excessive metal exposures.

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Cobalt and zinc showed a number of statistical interactions with variants from genes sharing biological pathways with a role in chronic diseases.

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The metabolic impact of metals combined with variation in redox-related genes might be large in the population, given metals widespread exposure.

Individual and joint effects of metal exposure on metabolic syndrome among Chinese adults

Growing evidence suggests that metal exposure contributes to metabolic syndrome (MetS), but little is known about the effects of combined exposure to metal mixtures. This cross-sectional study included 3748 adults who were recruited from the Medical Physical Examination Center of Tongji Hospital, Wuhan, China. The levels of 21 metal(loid)s in urine were measured by inductively coupled plasma mass spectrometry. MetS was diagnosed according to National Cholesterol Education Program's Adult Treatment Panel III recommendations. Multivariate logistic regression model was uesd to explore the effects of single-metal and multi-metal exposures. The elastic net (ENET) regularization with an environmental risk score (ERS) was performed to estimate the joint effects of exposure to metal mixtures. A total of 636 participants (17%) were diagnosed with MetS. In single metal models, MetS was positively associated with zinc (Zn) and negatively associated with nickel (Ni). In multiple metal models, the associations remained significant after adjusting for the other metals. In the joint association analysis, the ENET models selected Zn as the strongest predictor of MetS. Compared to the lowest quartile, the highest quartile of ERS was associated with an elevated risk of MetS (OR = 3.72; 95% CI: 2.77, 5.91; P-trend < 0.001). Overall, we identified that the combined effect of multiple metals was related to an increased MetS risk, with Zn being the major contributor. These findings need further validation in prospective studies.

Association between serum zinc concentrations and metabolic risk factors among Chinese children and adolescents

The aim of the present study was to examine whether serum Zn concentrations were associated with metabolic risk factors in Chinese children and adolescents. This was a cross-sectional study including 3241 participants, aged 6 to 17 years, from Jiangsu, China. Metabolic risk factors included fasting glucose (FG), total cholesterol (TC), TAG, HDL-cholesterol, LDL-cholesterol, systolic blood pressure and diastolic blood pressure. Data were analysed using multi-variable linear regression and generalised additive models, which were adjusted for age, sex, high-sensitive C-reactive protein, estimated glomerular filtration rate, BMI and region of residence, to assess the associations of serum Zn concentrations with metabolic risk factors. We observed a negative association between serum Zn concentrations and FG (coefficient = -0·532; 95 % CI -0·569, -0·495; P < 0·001). Moreover, TC (coefficient = 0·175; 95 % CI 0·127, 0·222; P < 0·001), HDL-cholesterol (coefficient = 0·137; 95 % CI 0·082, 0·193; P < 0·001) and LDL-cholesterol (coefficient = 0·195; 95 % CI 0·128, 0·263; P < 0·001) were found to be positively associated with Zn levels. A generalised additive model showed that the negative association between serum Zn and FG was weak at lower serum Zn concentrations and was stronger with the increase in serum Zn concentrations. Additionally, a U-shaped association between serum Zn and TAG was observed. Serum Zn concentrations were associated with FG, TC, TAG, HDL-cholesterol and LDL-cholesterol levels in Chinese children and adolescents. Lower levels of serum Zn were more likely related to a poor metabolic status.

Genetically predicted selenium is negatively associated with serum TC, LDL-C and positively associated with HbA1C levels

BACKGROUND & AIMS

Pervious epidemiological evidence on the associations of selenium, zinc with lipid profile and glycemic indices was contradictory. The aim of this study was to investigate whether selenium and zinc were casually associated with lipid profile and glycemic indices using mendelian randomization (MR) analysis.

METHOD

A two-sample MR was used to evaluate the causal-effect estimations. Summary statistics for selenium, zinc, lipids and glycemic indices were retrieved from previous large-scale genome-wide association study (GWAS). Single nucleotide polymorphisms (SNPs) that independently and strongly associated with the selenium and zinc were selected as the instrumental variables. The casual estimates were calculated using inverse variance weighted method (IVW), with weighted median, MR-Egger, and MR-PRESSO test as sensitivity analysis, respectively.

RESULTS

In the standard IVW analysis, per SD increment in selenium was associated with an 0.077 mmol/L decrease of TC (95 %CI: -0.102,-0.052) and 0.074 mmol/L of LDL-C (95 %CI: -0.1,-0.048). Suggestive casual associations were found between selenium and insulin or HbA1c. With IVW method, per SD increase in selenium was associated with an 0.023 mmol/L increase of insulin (95 %CI: 0.001,0.045), and an 0.013 mmol/L increase of HbA1c (95 %CI: 0.003,0.023). The results were robust in the sensitivity analysis. Zinc was not casually associated with any of lipid and glycemic markers.

CONCLUSION

Our MR analysis provides evidence of the potential causal effect of Se on beneficial lipid profile, including decreased TC and LDL-C. Furthermore, suggestive casual evidence was suggested between Se and increased serum HbA1c levels. Careful consideration is required for the protective effects of Se supplementation. No casual-effect association was found between Zn and any indices of the lipid and glucose parameters.

Associations Between Serum Multiple Metals Exposures and Metabolic Syndrome: a Longitudinal Cohort Study

Although many studies have confirmed metabolic syndrome (MetS) is correlated with metal exposures, few studies have elucidated the associations of multiple metals with MetS risk. We aim to explore the relationship between serum 22 metals and MetS. We determined serum 22 metals using ICP-MS and used LASSO regression to select metals independently related with MetS to construct multiple-metals model. We further explored the dose-response relationship between positive metals and MetS by the restricted cubic spline regression. After screening by LASSO regression, serum 11 metals were selected to construct multiple-metals model in cross-sectional analysis, while 5 metals in longitudinal analysis. In the 11-metal model, only tin and zinc were associated with MetS in cross-sectional analysis (OR_tin = 2.22, 95% CI:1.43, 3.45; OR_zinc = 2.17, 95% CI: 1.42, 3.32; both P_trend < 0.05). Besides, the same results were found in the 5-metal model in longitudinal analysis (HR_tin = 1.66, 95% CI: 0.87, 3.17; HR_zinc = 1.83, 95% CI: 1.07, 3.14; both P_trend < 0.05). Moreover, there were positive linear relationships between serum tin and zinc concentrations and the increasing risk of MetS (both P_overall < 0.05, P_{non-linearity} > 0.05). Furthermore, the interaction between high tin and high zinc was also associated with increasing MetS risk (P_interaction < 0.05). We found that serum tin and zinc were independently and interactively associated with MetS in the southern Chinese men. Our results suggested that high tin and zinc may be the risk factors of MetS.

Association between urinary metals levels and metabolic phenotypes in overweight and obese individuals

Epidemiologic studies suggest that circulating metals from the natural environment are linked with cardiometabolic health. However, few studies examined the relationship between multiple metals exposure and metabolic phenotypes, especially in obese individuals. We conducted a cross-sectional study to explore the association between 23 urinary metals and metabolic phenotypes in 1392 overweight and obese individuals (592 males, 800 females, mean age 43.1 ± 9.8 years). Participants were classified as metabolically unhealthy if they had ≥2 of the following metabolic abnormalities: elevated blood pressure, elevated fasting blood glucose, elevated triglycerides, and reduced high-density lipoprotein cholesterol. Odds ratios (ORs) of unhealthy metabolic phenotypes for metal levels categorized into tertiles were assessed using logistic regression models. Five metals (barium, copper, iron, uranium, and zinc) were associated with unhealthy metabolic phenotypes in single-metal models, while in the multiple-metal model, only zinc and zinc-copper ratio remained significant. The ORs (95% CIs) comparing extreme tertiles were 2.57 (1.69, 3.89) for zinc and 1.68 (1.24, 2.27) for zinc-copper ratio after adjustment for confounders (both p-trends were <0.001). The numbers of metabolic abnormalities significantly increased with the levels of zinc and the zinc-copper ratio increased. Similar associations were observed with metabolic syndrome risk. High levels of urinary zinc were positively associated with elevated fasting blood glucose (p-trend < 0.001) and elevated triglycerides (p-trend = 0.003). The results suggest that urinary zinc and zinc-copper ratio are positively associated with increased risk of unhealthy metabolic phenotype. Further prospective studies with a larger sample size are required to verify these findings.

Nutritional Effects of Zinc on Metabolic Syndrome and Type 2 Diabetes: Mechanisms and Main Findings in Human Studies

Zinc (Zn) plays crucial roles in mammalian metabolism. There is increasing interest about the potential beneficial effects of Zn on the prevention or treatment of non-communicable diseases. This review critically analyzes the information related to the role of Zn on the metabolic syndrome (MetS) as well as type 2 diabetes (T2D), and summarizes the biological basis of these potential effects of Zn. There are several mechanisms by which Zn may help to prevent the development or progression of MetS and T2D, respectively. Zn is involved in both insulin secretion and action in peripheral tissues. Specifically, Zn has insulin-mimetic properties that increase the activity of the insulin signaling pathway. Zn modulates long-chain polyunsaturated fatty acids levels through its action on the absorption of essential fatty acids in the intestine and its subsequent desaturation. Zn is also involved in both the assembly of chylomicrons and lipoproteins as well as their clearance, and thus, plays a role in lipolysis regulation. Finally, Zn has been found to play a role in redox metabolism, and in turn, on blood pressure. The evidence related to the association between Zn status and occurrence of MetS is inconsistent. Although there are several studies reporting an inverse relationship between Zn status or dietary Zn intake and MetS prevalence, others found a direct relationship between Zn status and MetS prevalence. Intervention studies also provide confusing information about this issue, making it hard to reach firm conclusions. Zn as part of the treatment for patients with T2D has been shown to have positive responses in terms of glucose control outcomes, but only among those with Zn deficiency.

Proper zinc evaluation in clinical practice: Effect of sample type and it's stability

Zinc (Zn) is a ubiquitous element that plays a vital role in the growth and development of human body. Traditionally, Zn has been measured in plasma samples using "trace element" dedicated sampling tubes. However, the recent increase in its assessment leads to the need to use others than plasma samples and the use of sera could be a justified and valid alternative. We evaluated the differences between plasma and serum, for Zn quantification. 307 blood paired samples from patients enrolled for the treatment of obesity-related pathology at our out-patient department were assessed. The quantification of Zn was performed by Flame atomic absorption spectroscopy. Using 123 serum samples randomly selected from our own biobank and stored at -80 °C for 5 years, we further investigated the long-term stability of serum Zn. The mean result for Zn was 77.8 ± 13.2 μg·dL^-1 and 77.4 ± 12.8 μg·dL^-1, respectively for plasma and for serum, (p = 0.43). Bland-Altman analyses demonstrated excellent concordance of the assay in the two different blood matrices. The mean difference ± SD between serum and plasma matrices was 0.32 ± 3.40 μg·dL^-1. The assessment of serum Zn long-term stability indicated a significant change after 5 years storage. The mean value was 74.2 ± 10.9 μg·dL^-1 for fresh samples and 83.3 ± 10.9 μg·dL^-1 after 5 years of storage at -80 °C, corresponding to a mean difference of +9.1 μg·dL^-1(+10,9%, p < 0.05). The increase in Zn values described after long-term storage has to be considered though that should not have a significant clinical value. In conclusion, the routine measurement of Zn can be made in an accurate way using a serum sample, without the need for a specific tube for trace elements assessment.

Relationship Between Serum Zinc Level and Metabolic Syndrome: A Meta-Analysis of Observational Studies

Objective: This research sought to summarize the evidence regarding the relationship between serum zinc level and metabolic syndrome (MetS).Methods: The electronic databases of PubMed, Web of Science, and Embase were searched up to October 2017 for observational studies on the association between serum zinc level and MetS. The standard mean difference (SMD) and its corresponding 95% confidence interval (CI) of the serum zinc level for MetS versus control participants were calculated. In addition, the pooled odds ratio (OR) and relative risk (RR) of MetS for the highest versus lowest category of serum zinc level, as well as their corresponding 95% CI, were also calculated.Results: A total of 11 observational studies (8 cross-sectional, 1 case-control, and 2 cohort studies) were included in this meta-analysis. The combined SMD demonstrated that the serum zinc level in MetS was higher than that in control participants (SMD = 0.11; 95% CI, 0.03-0.19; p = 0.009). Moreover, the overall multivariable-adjusted RR showed that the increased serum zinc level was associated with a higher risk of MetS (RR = 1.82; 95% CI, 1.33-2.50; p < 0.001). On the contrary, the overall multivariable-adjusted OR showed that there was no significant relationship between serum zinc level and MetS (OR = 1.00; 95% CI, 0.99-1.01; p = 0.841).Conclusions: Although the serum zinc level in participants with MetS was significantly higher than that in control ones, the existing evidence was still insufficient to conclude a definite relationship between serum zinc level and MetS. More well-designed prospective cohort studies are needed to elaborate the concerned issues further.