Associations of long-term cadmium exposure with peripheral white blood cell subtype counts and indices in residents of cadmium-polluted areas

Adverse effects of cadmium on lymphoid organs, immune cells, and immunological responses

Humans and animals possess robust immune systems to safeguard against foreign pathogens. However, recent reports suggest a greater incidence of immunity breakdown due to exposure to environmental pollutants, with heavy metals emerging as potential candidates in such immuno-toxicological studies. While we have extensive data on the general toxicity resulting from exposure to heavy metals, comprehensive documentation of their role as immune disruptors remains scarce. Cd (Cadmium) exerts immunomodulation by interfering with immune organs and cells, leading to altered structure, physiology, and function, thereby inducing symptoms of immune deregulation, inflammation and/or autoimmunity. This review aims to summarize the link between Cd exposure and immune dysfunction, drawing from case studies on exposed human subjects, as well as research conducted on various model organisms and in-vitro culture systems.

Association of Exposure to Heavy Metal Mixtures with Systemic Immune-Inflammation Index Among US Adults in NHANES 2011-2016

In reality, people are often co-exposed to multiple heavy metals; however, current research has focused on the association between individual heavy metals and inflammation. Therefore, it is more relevant to explore the combined effects of multiple heavy metal exposure on inflammation. The study included data from the National Health and Nutrition Examination Survey (NHANES), 2011-2016. The systemic immune-inflammation index (SII) was used to reflect systemic immune-inflammation status. In this study, single variable models were used to assess the linear and non-linear relationships between single heavy metal exposures and SII. To analyze the combined effect of mixed heavy metals exposure on SII, we constructed three statistical models, including weighted quantile sum (WQS) regression, quantile-based g computation (qgcomp), and Bayesian kernel machine regression (BKMR). The single-exposure analysis found positive associations between multiple heavy metals and SII, while mercury in blood was negatively associated with SII, and U-shaped correlations were observed between blood lead, urine barium and strontium, and SII. In the WQS model, SII increased significantly with increasing concentrations of mixed heavy metals, while consistent results in the qgcomp model, but not statistically significant. In the BKMR model, exposure to heavy metal mixtures was positively associated with SII, with mercury, cadmium, and cobalt in urine contributing the most to the mixed exposure. In addition, synergistic and antagonistic effects between heavy metals on increasing SII were found in our study. In summary, our results reveal that combined exposure to multiple heavy metals is positively associated with SII in the US adults.

Association between multiple-heavy-metal exposures and systemic immune inflammation in a middle-aged and elderly Chinese general population

BACKGROUND

Exposure to heavy metals alone or in combination can promote systemic inflammation. The aim of this study was to investigate potential associations between multiple plasma heavy metals and markers of systemic immune inflammation.

METHODS

Using a cross-sectional study, routine blood tests were performed on 3355 participants in Guangxi, China. Eight heavy metal elements in plasma were determined by inductively coupled plasma mass spectrometry. Immunoinflammatory markers were calculated based on peripheral blood WBC and its subtype counts. A generalised linear regression model was used to analyse the association of each metal with the immunoinflammatory markers, and the association of the metal mixtures with the immunoinflammatory markers was further assessed using weighted quantile sum (WQS) regression.

RESULTS

In the single-metal model, plasma metal Fe (log10) was significantly negatively correlated with the levels of immune-inflammatory markers SII, NLR and PLR, and plasma metal Cu (log10) was significantly positively correlated with the levels of immune-inflammatory markers SII and PLR. In addition, plasma metal Mn (log10 conversion) was positively correlated with the levels of immune inflammatory markers NLR and PLR. The above associations remained after multiple corrections. In the mixed-metal model, after WQS regression analysis, plasma metal Cu was found to have the greatest weight in the positive effects of metal mixtures on SII and PLR, while plasma metals Mn and Fe had the greatest weight in the positive effects of metal mixtures on NLR and LMR, respectively. In addition, blood Fe had the greatest weight in the negative effects of the metal mixtures for SII, PLR and NLR.

CONCLUSION

Plasma metals Cu and Mn were positively correlated with immunoinflammatory markers SII, NLR and PLR. While plasma metal Fe was negatively correlated with immunoinflammatory markers SII, NLR, and PLR.

The single and mixed impacts of cadmium, cobalt, lead, and PAHs on systemic immunity inflammation index in male and female

Background

Studies on the association between mixed exposure to common pollutants such as cadmium (Cd), cobalt (Co), lead (Pb), and polycyclic aromatic hydrocarbons (PAHs) with Systemic Immune Inflammatory Index (SII), a novel hemocyte-based inflammatory marker, have not been reported. This study explored the relationship between co-exposure to Cd, Co, Pb, PAHs, and SII.

Methods

In this study, we used data from the National Health and Nutrition Examination Survey and enrolled adults with complete information on Cd, Co, Pb, PAHs, and SII. The linear regression was used to analyze the association of single pollutants with SII. Furthermore, a Bayesian Kernel Machine Regression analysis and a generalized weighted quantile sum regression analysis were used to analyze the association between mixed exposure to Cd, Co, Pb, and six PAHs and SII. We also separated males and females and analyzed the different effects of pollutants on SII, respectively.

Results

5,176 participants were included in the study. After adjusting for age, gender, race, education, smoking, drinking, physical activity, and sedentary, Cd, Co, 1-OHN, 2-OHN and 2-OHF were positive with SII in the total population. Compared with the 50th percentile, the joint effect of pollutants on SII was positive. In the total population, males, and females, the top contaminant with the highest effect weights on SII were Co, Cd, and 1-OHN, respectively. The result of interaction analysis showed that the low concentrations of Cd had an elevation effect on SII in males.

Conclusion

This study found a positive association of mixed exposure to Cd, Co, Pb, and six PAHs with SII, which occurred mainly in females.

Serum albumin mediates the associations between heavy metals and two novel systemic inflammation indexes among U.S. adults

BACKGROUND

The effects of heavy metal exposure on immunological function have sparked widespread concern, but unequivocal evidence on the association between mixed metal exposure and novel systemic inflammatory indexes remains scarce.

OBJECTIVES

This study aimed to analyze the associations of heavy metals with two novel systemic inflammation indexes and the mediated effects of serum albumin.

METHODS

Nineteen metals were detected among 4082 U.S. adults based on the NHANES. A linear regression, restricted cubic splines (RCS) regression, weighted quantile sum (WQS), Quantile-based Gcomputation (qgcomp), and Bayesian kernel machine regression (BKMR) were conducted to evaluate the associations of single metal and mixed metals with systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) levels, respectively. A series of subgroup analyses were used to identify potentially vulnerable populations. Furthermore, we conducted mediation analyses to investigate the mediated effects of serum albumin on the associations of metals with SII and SIRI.

RESULTS

In the single-exposure model, exposure to various metals such as urinary Co, As, and serum Zn, Cu was associated with SII and SIRI (PFDR<0.05). Simultaneously, the above metals were linear positively correlated with SII and SIRI. Mixed-exposure analyses consistently showed that overall mixed urinary metal levels were positively pertinent for SII and SIRI levels, and the metal Co played a significant role in the urinary metal mixtures. Subgroup analyses showed that exposure to urinary Cd in men and elderly people increased SII and SIRI levels. The results of mediation analyses suggested the association of urinary metal mixture with SII and SIRI was mediated by albumin, and the proportion of mediation was 14.45% and 9.49%, respectively.

CONCLUSIONS

Our findings suggested that metal exposure is strongly associated with the levels of system inflammation indexes and that serum albumin is, in part, a mediator of this association.

Independent association of blood cadmium with subclinical lower extremity atherosclerosis: An observational study based on dose-response analysis

BACKGROUND

Atherosclerosis is an increasingly public health issue globally. Previous studies have showed a causal link between heavy metal exposure and atherosclerosis. However, the association of cadmium concentration with subclinical lower extremity atherosclerosis (SLEA) remains unclear.

AIMS

To investigate the association of blood cadmium with SLEA and its extent, and further analyze the potential dose-response relationship.

METHODS

Blood cadmium concentration was measured using inductively coupled plasma mass spectrometry. SLEA and its extent were assessed by ultrasound diagnosis system. Multivariate models were applied to evaluate the association of blood cadmium with SLEA and its extent. Restricted cubic splines were performed to explore the potential dose-response relationship.

RESULTS

This observational study consisted of 1664 participants from cardiovascular outpatient, with an average age of 62.4 years and 1218 (73.2%) men. When blood cadmium was included as a categorical variable in multivariate models, logistic regression analysis showed that high quartile in blood cadmium was an independent risk factor of SLEA (OR = 2.704, 95%CI 1.866-3.919). After log-transformed for SLEA extent parameters, linear regression analysis indicated that high quartile in blood cadmium was significantly associated with higher Crouse score (GMR = 1.21, 95%CI 1.15-1.28), plaque maximum thickness (GMR = 1.13, 95%CI 1.09-1.18) and diseased vessel count (GMR = 1.14, 95%CI 1.10-1.19), respectively. When blood cadmium was used as a continuous variable in restricted cubic splines, the dose-response relationship presented a positive progression in SLEA (P = 0.302), plaque maximum thickness (P = 0.145) and diseased vessel count (P = 0.055) apparently that did not deviate from linearity.

CONCLUSIONS

Blood cadmium exhibited an independent association with SLEA, and this dose-response relationship was progressive without significant departure from linearity.