Serum essential trace elements and toxic metals in Chinese diabetic retinopathy patients

Association between serum heavy metal levels and diabetic retinopathy in NHANES 2011-2020

The present study utilized the National Health and Nutrition Examination Survey (NHANES) database to examine the relationship between serum levels of heavy metals and Diabetic retinopathy (DR) in individuals aged over 30 years with type 2 diabetes mellitus (T2DM) in the United States. A cross-sectional analysis was conducted on 1583 individuals with T2DM from the NHANES 2011-2020, including 331 individuals in the DR group and 1252 individuals in the non-DR group. We collected data on serum levels of heavy metals, DR, and serum albumin for descriptive statistics, linear regression, and logistical regression analysis. After adjusting for age, gender, race and other factors, there was no statistically significant association between blood cadmium, selenium, mercury, or lead and DR. However, serum manganese (Mn) and DR had a significant negative association (β = - 0.2045, 95% CI = - 0.3484, - 0.0606). Serum albumin partially modulated the indirect influence of serum Mn on the incidence of DR, accounting for 12.80% of the association between serum Mn and DR. There was a negative association between serum Mn levels and the prevalence of DR in people with T2DM. Mn intake at least in this study has a little influence on the onset and development of DR.

The impact of multiple metals exposure on the risk of developing proliferative diabetic retinopathy in Anhui, China: a case-control study

Through multiple different pathways, the environmental multiple metals make their ways to the human bodies, where they induce different levels of the oxidative stress response. This study further investigated the impact of multiple-metal exposure on the risk of developing proliferative diabetic retinopathy (PDR). We designed a case-control study with type 2 diabetic patients (T2D), in which the case group was the proliferative diabetic retinopathy group (PDR group), while the control group was the non-diabetic retinopathy group (NDR group). Graphite furnace atomic absorption spectrometry (GFAAS) and inductively coupled plasma optical emission spectrometry (ICP-OES) were used to detect the metal levels in our participants' urine samples. The least absolute shrinkage and selection operator (LASSO) regression approach was used to include these representative trace elements in a multiple exposure model. Following that, logistic regression models and Bayesian kernel machine regression (BKMR) models were used to describe the effect of different elements and also analyze their combined effect. In the single-element model, we discovered that lithium (Li), cadmium (Cd), and strontium (Sr) were all positively related to PDR. The multiple-exposure model revealed a positive relationship between Li and PDR risk, with a maximum quartile OR of 2.80 (95% CI: 1.10-7.16). The BKMR model also revealed that selenium (Se) might act as a protective agent, whereas magnesium (Mg), Li, and Cd may raise the risk of PDR. In conclusion, our study not only revealed an association between exposure to multiple metals and PDR risk but it also implied that urine samples might be a useful tool to assess PDR risk.

The associations of non-essential metal mixture with fasting plasma glucose among Chinese older adults without diabetes

The evidence about the effect of non-essential metal mixture on fasting plasma glucose (FPG) levels among older adults without diabetes is limited. This study aims to estimate the individual and joint relationship between five non-essential metals and FPG levels in Chinese older adults without diabetes. This study included 2362 older adults without diabetes. Urinary concentrations of five non-essential metals, i.e., cesium (Cs), aluminum (Al), thallium (Tl), cadmium (Cd), and arsenic (As), were detected by inductively coupled plasma mass spectrometry (ICP-MS). The associations of single metals and the metal mixture with FPG levels were assessed using linear regression and Bayesian kernel machine regression (BKMR) models, respectively. Adjusted single-metal linear regression models showed positive associations of urinary Al (β = 0.016, 95%CI: 0.001-0.030) and Cs (β = 0.018, 95%CI: 0.006-0.031) with FPG levels. When comparing the 2th, 3th, and 4th quartiles of urine Cs to its 1th quartile, the significant associations between Cs and FPG levels were found and presented as an "inverted U" trend (βQ2 vs. Q1: 0.034; βQ3 vs. Q1:0.054; βQ4 vs. Q1: 0.040; all P<0.05). BKMR analyses showed urinary level of Cs exhibited an "inverted U" shape association with FPG levels. Moreover, the FPG levels increased linearly with the raised levels of the non-essential metal mixture, and the posterior inclusion probability (PIP) of Cs was the highest (0.92). Potential positive interaction of As and Cs on FPG levels was found in BKMR model. Stratified analysis displayed significant interactions of hyperlipidemia and urine Cs or Tl on FPG levels. An inverse U-shaped association between Cs and FPG was found, individually and as mixture. The FPG levels increased with the raised levels of the non-essential metal mixture, and Cs was the most contributor to FPG levels. Further research is required to confirm the correlation between non-essential metals and FPG levels and to clarify the underlying mechanisms.

Comparison of selenium levels between diabetic patients with and without retinopathy

Background/Aim: Diabetic retinopathy is a common ailment that causes visual impairment among adults, and evidence suggests that oxidative stress plays a significant role in its pathogenesis. The objective of this study was to examine the potential association between selenium deficiency and an increased risk of diabetic retinopathy among individuals with type 2 diabetes mellitus. Methods: This study was a prospective case-control study. 115 patients with a diagnosis of type 2 diabetes mellitus were included. The patients were divided into groups with and without retinopathy. No subgroups were made according to the level of retinopathy. The aim was to compare the serum selenium level of patients between groups. Therefore, other variables that may contribute to the development of retinopathy were also recorded. The duration of diabetes, medications used, and glycosylated hemoglobin levels were recorded. The retinopathy group included 47 patients, and the non-retinopathy group included 68 patients. Selenium levels were measured in plasma samples. Results: The mean selenium level of the retinopathy group (70.11 [17.28] μg/l) was significantly lower than that of the non-retinopathy group (80.20 [19.10] μg/l) (P=0.005). The median duration of diabetes mellitus was significantly higher in the retinopathy group than in the non-retinopathy group (10 [1-25] and 6 [1-21], respectively; P=0.002). Logistic regression analyses showed that higher levels of blood selenium were independent preventive factors against the occurrence of retinopathy (OR [95% CI]: 0.965 [0.939-0. 991]). The duration of diabetes mellitus was an independent risk factor for retinopathy occurrence [OR (95% CI): 1.131 (1.050-1.219)]. One unit increase in selenium level was associated with a unit decrease in diabetic retinopathy of 0.965 (0.939-0.991). Conclusion: Our research revealed a correlation between the duration of diabetes and the incidence of diabetic retinopathy. Furthermore, a notable difference was observed in blood selenium levels between patients with diabetic retinopathy and those without it. Specifically, patients with diabetic retinopathy had lower plasma selenium levels compared to the control group. These findings have potential implications for the treatment or prevention of diabetic retinopathy, but more research is needed to determine the efficacy of selenium supplementation for diabetic patients with or without microvascular complications. Future studies should investigate the effect of selenium deficiency on different subtypes of diabetic retinopathy and the impact of selenium supplementation in this patient population.

Cadmium exposure and risk of diabetes and prediabetes: A systematic review and dose-response meta-analysis

BACKGROUND

Cadmium exposure has been associated with increased diabetes risk in several studies, though there is still considerable debate about the magnitude and shape of the association.

OBJECTIVE

To perform a systematic review and meta-analysis of observational studies investigating the relation between cadmium exposure and risk of type 2 diabetes and prediabetes, and to summarize data on the magnitude and shape of the association.

DATA SOURCE

After conducting an online literature search through October 1, 2021, we identified 42 eligible studies investigating the association between cadmium exposure and risk of diabetes and prediabetes.

STUDY ELIGIBILITY CRITERIA

We included studies that assessed cadmium exposure through biomarker levels; examined type 2 diabetes or prediabetes among outcomes; and reported effect estimates for cadmium exposure for meta-analysis only.

STUDY APPRAISAL AND SYNTHESIS METHODS

Studies were evaluated using ROBINS-E risk of bias tool. We quantitively assessed the relation between exposure and study outcomes using one-stage dose-response meta-analysis with a random effects meta-analytical model.

RESULTS

In the meta-analysis, comparing highest-versus-lowest cadmium exposure levels, summary relative risks (RRs) for type 2 diabetes were 1.24 (95% confidence interval 0.96-1.59), 1.21 (1.00-1.45), and 1.47 (1.01-2.13) for blood, urinary, and toenail matrices, respectively. Similarly, there was an increased risk of prediabetes for cadmium concentrations in both urine (RR = 1.41, 95% CI: 1.15-1.73) and blood (RR = 1.38, 95% CI: 1.16-1.63). In the dose-response meta-analysis, we observed a consistent linear positive association between cadmium exposure and diabetes risk, with RRs of 1.25 (0.90-1.72) at 2.0 µg/g of creatinine. Conversely for blood cadmium, diabetes risk appeared to increase only above 1 µg/L. Prediabetes risk increased up to approximately 2 µg/g creatinine above which it reached a plateau with RR of 1.42 (1.12-1.76) at 2 µg/g creatinine.

LIMITATIONS AND CONCLUSIONS

This analysis provides moderate-certainty evidence for a positive association between cadmium exposure (measured in multiple matrices) and risk of both diabetes and prediabetes.

Environmental pollution and diabetes mellitus

Diabetes mellitus (DM) is a chromic metabolic disease that affects a large segment of the population worldwide. Physical inactivity, poor nutrition, and genetic predisposition are main risk factors for disease development. In the last decade, it was clear to the scientific community that DM development is linked to a novel disease inducer that was later defined as diabetogenic factors of pollution and endocrine disrupting agents. Environmental pollution is exponentially increasing in uncontrolled manner in several countries. Environmental pollutants are of diverse nature and toxicities, including polyaromatic hydrocarbons (PAHs), pesticides, and heavy metals. In the current review, we shed light on the impact of each class of these pollutants and the underlined molecular mechanism of diabetes induction and biological toxicities. Finally, a brief overview about the connection between coronavirus disease 2019 and diabetes pandemics is presented.