Air pollution has become a major global threat to human health. Urbanization and industrialization over the past few decades have increased the air pollution. Plausible connections have been made between air pollutants and dementia. This study used machine learning algorithms (k-nearest neighbors, random forest, gradient-boosted decision trees, eXtreme gradient boosting, and CatBoost) to investigate the association between cognitive impairment and air pollution. Data from the Taiwan Biobank and 75 air-pollution-monitoring stations in Taiwan were analyzed to determine individual levels of exposure to air pollutants. The pollutants examined were particulate matter with a diameter of ≤ 2.5 μm (PM_2.5), nitrogen dioxide, nitric oxide, carbon monoxide, and ozone. The results revealed that the most strongly correlated with cognitive impairment were ozone, PM_2.5, and carbon monoxide levels with adjustment of educational level, age, and household income. The model based on these factors achieved accuracy as high as 0.97 for detecting cognitive impairment, indicating a positive association between air pollutions and cognitive impairment.

Exposure to heavy metals could lead to adverse health effects by oxidative reactions or inflammation. Some essential elements are known as reactors of anti-inflammatory enzymes or coenzymes. The relationship between tumor necrosis factor alpha (TNF-α) and heavy metal exposures was reported. However, the interaction between toxic metals and essential elements in the inflammatory response remains unclear. This study aimed to explore the association between arsenic (As), cadmium (Cd), lead (Pb), cobalt (Co), copper (Cu), selenium (Se), and zinc (Zn) in blood and TNF-α as well as kidney function. We enrolled 421 workers and measured the levels of these seven metals/metalloids and TNF-α in blood; kidney function was calculated by CKD-EPI equation. We applied weighted quantile sum (WQS) regression and group WQS regression to assess the effects of metal/metalloid mixtures to TNF-α and kidney function. We also approached the relationship between metals/metalloids and TNF-α by generalized additive models (GAM). The relationship of the exposure–response curve between Pb level and TNF-α in serum was found significantly non-linear after adjusting covariates (p < 0.001). Within the multiple-metal model, Pb, As, and Zn were associated with increased TNF-α levels with effects dedicated to the mixture of 50%, 31%, and 15%, respectively. Grouped WQS revealed that the essential metal group showed a significantly negative association with TNF-α and kidney function. The toxic metal group found significantly positive associations with TNF-α, serum creatinine, and WBC but not for eGFR. These results suggested Pb, As, Zn, Se, and mixtures may act on TNF-α even through interactive mechanisms. Our findings offer insights into what primary components of metal mixtures affect inflammation and kidney function during co-exposure to metals; however, the mechanisms still need further research.

Air pollutants are substances in the air that have harmful effects on humans and the ecological environment. Although slight elevations in carcinoembryonic antigen (CEA) are commonly observed in apparently healthy persons, potential associations between CEA levels and chronic low-grade inflammation induced by air pollution have yet to be documented. We conducted a community-based cross-sectional study to estimate the association between short-term exposure to ambient air pollution and the CEA. A total of 9728 participants from health examinations were enrolled for the analysis and linked with their residential air pollutant data including ozone (O₃), nitrogen dioxide (NO₂), carbon monoxide (CO), sulphur dioxide (SO₂), and particulate matter (PM₁₀). The results showed that every increase of 1 ppm O₃ significantly increased the mean differences of the CEA blood concentration by 0.005 ng/mL. Each increase of 1 ppm CO significantly reduced the mean differences of the CEA blood concentration by 0.455 ng/mL. Although smoking and alcohol drinking also increased the CEA levels, with adjustment of these confounders we identified a significant association between serum CEA in the general population and levels of the air pollutants O₃ and CO. In conclusion, the serum CEA concentrations and short-term air pollutants O₃ and CO exposure were found to have a significant relationship; however, its mechanism is still unclear. Moreover, long-term air pollution exposure and changes in CEA concentration still need to be further evaluated.

With the escalating global prevalence of metabolic syndrome (MetS), it is crucial to detect the high-risk population early and to prevent chronic diseases. Exposure to various metals has been indicated to promote MetS, but the findings were controversial, and the effect of genetic modification was not considered. Epidermal growth factor receptor (EGFR) was proposed to be involved in the pathway of metabolic disorders, and tumor necrotic factor-α (TNF-α) was regarded as an early inflammatory biomarker for MetS. This research aimed to analyze the impact of EGFR and TNF-α gene polymorphisms on the prevalence of MetS under environmental or occupational exposure to metals. We gathered data from 376 metal industrial workers and 639 non-metal workers, including physical parameters, biochemical data, and plasma concentrations of six metals. According to the genomic database of Taiwan Biobank, 23 single nucleotide polymorphisms (SNPs) on EGFR gene and 6 SNPs on TNF-α gene were incorporated in our research. We applied multivariable logistic regression to analyze the probability of MetS with various SNPs and metals. Our study revealed some susceptible and protective EGFR and TNF-α genotypes under excessive exposure to cobalt, zinc, selenium, and lead. Thus, we remind the high-risk population of taking measures to prevent MetS.

Exposure to metals may be associated with renal function impairment, but the effect modified by genetic polymorphisms was not considered in most studies. Epidermal growth factor receptor (EGFR) and tumor necrotic factor-α (TNF-α) play important roles in renal hemodynamics, and they have been reported to be associated with some renal diseases. The aim of our research is to explore whether genetic variations in EGFR and TNF-α have influence on renal function under exposure to various metals. This cross-sectional study consisted of 376 metal industrial workers, 396 participants of Taiwan Biobank, and 231 volunteers of health examinations. We identified 23 single nucleotide polymorphisms (SNPs) on the EGFR gene and 6 SNPs on the TNF-α gene, and we also measured their plasma concentration of cobalt, copper, zinc, selenium, arsenic, and lead. Multiple regression analysis was applied to investigate the association between various SNPs, metals, and renal function. Our results revealed some protective and susceptible genotypes under occupational or environmental exposure to metals. The individuals carrying EGFR rs2280653 GG might have declined renal function under excessive exposure to selenium, and those with EGFR rs3823585 CC, rs12671550 CC, and rs4947986 GG genotypes might be susceptible to lead nephrotoxicity. We suggest the high-risk population to prevent renal diseases.

When poisons enter the human body, tumor necrosis factor (TNF-α) will increase and cause damage to tissues through oxidative stress or inflammatory reaction. In previous studies, arsenic (As) has known to cause many health problems. Some studies have shown that As exposure is negatively correlated with estimated glomerular filtration rate (eGFR), or with the prevalence of proteinuria. At present, there are few studies focusing on the effects of As exposure and TNF-α single nucleotide polymorphism (SNP) to eGFR; thus, this study was intended to explore the interactions between TNF-α SNPs and plasma As and their effects on eGFR. A cohort of 500 adults, aged 30 to 70 years, was randomly selected from Taiwan Biobank (TWB). We used the gene chip to screen out seven SNPs of the TNF-α gene and used the results, combined with questionnaires, biochemical tests, and stored plasma samples from the TWB, for the analysis of As by inductively coupled plasma mass spectrometry (ICP-MS). After adjustments for BMI, hypertension, hyperlipidemia, kidney stones, and smoking habits, multiple regression statistics were performed to explore the interaction between SNPs and plasma As with eGFR. In this sample of the general population, plasma As had a significant association with the decline of eGFR (β (SE) = −7.92 (1.70), p < 0.0001). TNF-α gene SNP rs1800629 had the property of regulating TNF-α, which interacts with plasma As; individuals with the AG type had a significantly lower eGFR than those with the GG type, by 9.59 mL/min/1.73 m² (p < 0.05), which, regarding the dominant model, could infer that the A allele is a risk allele. SNP rs769177 had no interaction with plasma As; however, participants with the TT or TC type had significantly higher eGFR levels than the CC carriers, by 4.02 mL/min/1.73 m² (p < 0.05). While rs769176 interacted with plasma As, if a person with the TC type had a higher plasma As concentration, that would sustain higher eGFR. This study found that certain SNPs of the TNF-α gene would be robust to the decline of eGFR caused by As exposure. Still, we need further research to confirm the protective regulation mechanism of these SNPs.