Association between plasma and dietary trace elements and obesity in a rural Chinese population.

Trace elements may play an important role in obesity. This study aimed to assess the plasma and dietary intake levels of four trace elements, Mn, Cu, Zn and Se in a rural Chinese population, and analyse the relationship between trace elements and obesity. A cross-sectional study involving 2587 participants was conducted. Logistic regression models were used to analyse the association between trace elements and obesity; restricted cubic spline (RCS) models were used to assess the dose-response relationship between trace elements and obesity; the weighted quantile sum (WQS) model was used to examine the potential interaction of four plasma trace elements on obesity. Logistic regression analysis showed that plasma Se concentrations in the fourth quartile (Q4) exhibited a lower risk of developing obesity than the first quartile (Q1) (central obesity: OR = 0·634, P = 0·002; general obesity: OR = 0·525, P = 0·005). Plasma Zn concentration in the third quartile (Q3) showed a lower risk of developing obesity in general obesity compared with the first quartile (Q1) (OR = 0·625, P = 0·036). In general obesity, the risk of morbidity was 1·727 and 1·923 times higher for the second and third (Q2, Q3) quartiles of dietary Mn intake than for Q1, respectively. RCS indicated an inverse U-shaped correlation between plasma Se and obesity. WQS revealed the combined effects of four trace elements were negatively associated with central obesity. Plasma Zn and Se were negatively associated with obesity, and dietary Mn was positively associated with obesity. The combined action of the four plasma trace elements had a negative effect on obesity.

ApoE gene polymorphisms and metals and their interactions with cognitive function.

OBJECTIVE: To analyze the relationship between plasma metal elements, ApoE gene polymorphisms and the interaction between the two and impaired cognitive function in elderly population. METHOD: A stratified sample was drawn according to the age of the study population, and 911 subjects were included. Baseline information and health indicators were obtained, and cognitive function status was assessed by health examination, a general questionnaire and Mini-Mental Status Examination. Plasma metal elements were measured, and SNP typing was performed. Binary logistic regression was used to analyze the factors influencing cognitive function status and the association between the SNP genetic pattern of the ApoE gene and cognitive function. RESULTS: The differences in gene frequencies and genotype frequencies of the ApoE rs7412 and rs7259620 genotype frequencies were statistically different between the cognitive impairment group and the control group (P < 0.05). statistically differences were found for the codominant model in rs7412-TT compared with the CC genotype (OR = 3.112 (1.159-8.359), P = 0.024) and rs7259620-AA compared with the GG genotype (OR = 1.588 (1.007-2.504), P = 0.047). Statistically differences were found in the recessive models rs7412-TT compared with (CC + CT) (OR = 2.979 (1.112-7.978), P = 0.030), rs7259620-AA compared with (GG + GA), and rs405509-GG compared with (TT + TG) (OR = 1.548(1.022-2.344), P = 0.039) all of which increased the risk of developing cognitive impairment. The differences in plasma Fe, Cu, and Rb concentrations between the case and control groups were significant (P < 0.05). The regression results showed that the plasma Cd concentrations in the Q1 range was a protective factor for cognitive function compared with Q4 (0.510 (0.291-0.892), P = 0.018). Furthermore, there was a multiplicative interaction between the codominant and recessive models for the Q2 concentrations of Cd and the rs7259620 loci, and the difference was significant, indicating increased risk of developing cognitive impairment (codominant model OR = 3.577 (1.496-8.555), P = 0.004, recessive model OR = 3.505 (1.479-8.307), P = 0.004). There was also a multiplicative interaction between Cd and the recessive model at the rs405509 loci, and the difference was significant, indicating increased risk of developing cognitive impairment (OR = 3.169 (1.400-7.175), P = 0.006). CONCLUSION: The ApoE rs7412, rs7259620 and rs405509 loci were associated with cognitive impairment in the elderly population, and there was an interaction between plasma metalloid Cd and the rs7259620 and rs405509 loci that increased the risk of cognitive impairment in the elderly population.

Association between barium exposed, CYP19A1 and central obesity: A cross-sectional study in rural China.

BACKGROUND: obesity is a major risk factor for many metabolic diseases such as diabetes and cardiometabolic diseases. This study aimed to evaluate the association of plasma and urinary barium concentrations, CYP19A1 gene polymorphisms, and their interaction with central obesity in a rural Chinese population. METHODS: restricted cubic spline model was used to explore the dose-response relationship between barium and the risk of developing central obesity and waist circumference; logistic regression model was used to assess the association between barium, CYP19A1 gene polymorphisms and their interaction with central obesity. RESULTS: the results of the restricted cubic spline model showed that plasma barium concentration was linearly associated with the risk of developing central obesity and non-linearly associated with waist circumference. Logistic regression analysis showed that participants with Q4 plasma barium concentration exhibited a higher risk of central obesity compared to participants with Q1 barium concentration; participants carrying the rs10046-AA gene exhibited a lower risk of central obesity than those carrying the rs10046-G(GG+GA) gene; participants carrying the rs10046-GA genotype showed 1.754 times higher risk of central obesity than those carrying rs10046-GG+AA genotype. There was a significant interaction between plasma barium and CYP19A1 gene polymorphism on central obesity. CONCLUSION: the development of central obesity was associated with plasma barium and CYP19A1.

Associations of Dietary and Plasma Copper Levels with Liver Function in a Chinese Population.

The potential mechanisms underlying the association between copper (Cu) exposure and impaired liver function are unclear. This study aimed to investigate the potential associations of dietary Cu intake and plasma Cu levels with liver function biomarkers. A cross-sectional study was performed to assess liver function biomarkers-namely, levels of total bilirubin (TBIL), direct bilirubin (DBIL), indirect bilirubin (IBIL), alanine transaminase (ALT), and aspartate transaminase (AST)-in 2376 subjects in Guangxi, China. Dietary Cu intake was determined from a food frequency questionnaire containing 109 common foods. Plasma Cu concentrations were determined by inductively coupled plasma‒mass spectrometry. Multiple linear regression and multivariate restricted cubic splines (RCS) were used to evaluate the correlations of plasma Cu levels and dietary Cu levels with liver function biomarkers. The covariate-adjusted results of the linear regression analysis showed that plasma Cu levels were significantly negatively correlated with serum IBIL (ß = - 0.37), DBIL (ß = - 0.22), and TBIL levels (ß = - 0.32) (all p < 0.05), and dietary Cu was negatively correlated with serum AST levels (ß = - 0.12, p < 0.05). The RCS analysis further indicated a negative linear relationship between dietary Cu levels and AST levels. In summary, our results suggested that the plasma Cu level is associated with serum bilirubin levels and that dietary Cu intake is associated with serum AST levels. Further studies are needed to validate these associations and elucidate the underlying mechanisms.

Association of CYP19A1 Gene, Plasma Zinc, and Urinary Zinc with the Risk of Type 2 Diabetes Mellitus in a Chinese Population.

To explore the effects of CYP19A1 gene polymorphisms, plasma zinc, and urinary zinc levels and their interactions on type 2 diabetes mellitus (T2DM) in residents of Gongcheng County, Guangxi, China. The case-control study was used for the investing. The MassARRAY System was applied to genotype the CYP19A1 genes rs752760, rs10046, rs10459592, and rs700518 in 540 study subjects. Plasma and urinary zinc concentrations were measured by inductively coupled plasma mass spectrometry (ICP-MS). Conditional logistic regression showed that rs752760 and plasma zinc were associated with T2DM risks with ORs of 0.593 (95% CI: 0.371-0.948) and 0.563 (95% CI: 0.356-0.889), respectively. Unconditional logistic regression analysis showed an association between urinary zinc levels and the risk of T2DM as well, with an OR of 0.352 (95% CI: 0.212-0.585). The results of the multiplicative interaction model showed that the rs752760 T allele was associated with a significantly reduced risk of T2DM with moderate/low plasma zinc levels, with ORs of 0.340 (95% CI: 0.161-0.715) and 0.583 (95% CI: 0.346-0.981), respectively, and the rs752760 T allele was also associated with a significantly decreased risk of T2DM with moderate/low urinary zinc levels, with ORs of 0.358 (95% CI: 0.201-0.635) and 0.321 (95% CI: 0.183-0.562), respectively. CYP19A1 rs752760 T allele and moderate/low plasma/urinary zinc levels reduce the risk of T2DM.

Sex-Specific Associations of Urinary Metals with Renal Function: a Cross-sectional Study in China.

BACKGROUND: Extensive studies have revealed the link between heavy metals and CKD. Compared to single meta-elements, mixture of metals reflect real-life metals exposure scenarios and are of interest. However, the mechanism of action of metal mixture on renal function is unclear. METHODS: This study aimed to explore the potential relationship between urinary arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and chromium (Cr) contents with estimated glomerular filtration rate (eGFR) levels in 2775 participants. The levels of metals in urine were determined by inductively coupled plasma-mass spectrometry. We used linear regression models and the Bayesian kernel machine regression (BKMR) to evaluate the association between metals and eGFR levels. RESULTS: In linear regression analysis, urinary As (ß = 2.723, 95%CI: 0.29, 5.157) and Pb (ß = 3.081, 95%CI: 1.725, 4.438) were positively associated with eGFR in the total population. In the BKMR model, a mixture of the five metals had a positive joint effect on eGFR levels, while Pb (PIP = 0.996) contributed the most to eGFR levels. Pb was positively associated with eGFR levels in the total participants and women. As was positively correlated with eGFR levels in women. Pb and eGFR levels were positively correlated when the other metals were set at 25th, 50th, and 75th percentiles. CONCLUSIONS: To the best of our knowledge, all five metals mixed exposure was positively associated with eGFR. Pb showed more important effects than the other four metals in the mixture, especially in women.

Association of Dietary and Plasma Magnesium with Glycaemic Markers in a Chinese Population.

Certain metals play a role in the pathogenesis of diabetes. This study aimed to investigate the potential association of plasma magnesium (Mg) and dietary intake of Mg with glycaemic markers. A cross-sectional study was conducted on 2373 subjects in Guangxi, China. Dietary Mg was obtained through a food frequency questionnaire containing 109 common foods. Plasma Mg concentration was determined by inductively coupled plasma mass spectrometry. Multiple linear regression combined with multivariable restricted cubic spline (RCS) functions was applied to evaluate the association of plasma Mg and dietary Mg with haemoglobin A1c (HbA1c) and fasting plasma glucose (FPG). In linear regression, dietary Mg was significantly associated with FPG in the overall population (ß = - 0.087, P < 0.05) and in women (ß = - 0.098, P < 0.05). Plasma Mg was significantly associated with FPG in the overall population (ß = - 0.096, P < 0.05) and in men (ß = - 0.110, P < 0.05) and women (ß = - 0.088, P < 0.05). In the RCS model, no non-linear association was found between dietary and plasma Mg and HbA1c levels. Dietary and plasma Mg are significantly negatively associated with fasting glucose.

Association between combined exposure to plasma heavy metals and dyslipidemia in a chinese population.

BACKGROUND: Exposure to heavy metals in the environment is widespread, while the relationship between combined exposure to heavy metals and dyslipidemia is unclear. METHODS: A cross-sectional study was performed, and 3544 participants aged 30 years or older were included in the analyses. Heavy metal concentrations in plasma were based on inductively coupled plasma‒mass spectrometry. The relationship between heavy metals and dyslipidemia was estimated by logistic regression. BKMR was used to evaluate metal mixtures and their potential interactions. RESULTS: In logistic regression analysis, participants in the fourth quartile of Fe and Zn (Fe > 1352.38 µg/L; Zn > 4401.42 µg/L) had a relatively higher risk of dyslipidemia (Fe, OR = 1.13, 95% CI: 0.92,1.38; Zn, OR = 1.30, 95% CI: 1.03,1.64). After sex stratification, females in the third quartile of plasma Zn (1062.05-4401.42 µg/L) had a higher relative risk of dyslipidemia (OR = 1.75, 95% CI: 1.28, 2.38). In BKMR analysis, metal mixtures were negatively associated with dyslipidemia in females when all metal concentrations were above the 50th percentile. In the total population (estimated from 0.030 to 0.031), As was positively associated with dyslipidemia when other metals were controlled at the 25th, 50th, or 75th percentile, respectively, and As was below the 75th percentile. In females (estimated from - 0.037 to -0.031), Zn was negatively associated with dyslipidemia when it was above the 50th percentile. CONCLUSION: This study indicated that As was positively associated with dyslipidemia and that Zn may be negatively associated with dyslipidemia in females. Combined metal exposure was negatively associated with dyslipidemia in females. Females with low plasma Zn levels are more likely to develop dyslipidemia and should receive more clinical attention in this population.

Associations Between Plasma Metals and Cognitive Function in People Aged 60 and Above.

The objective of the study was to explore the relationship between the plasma levels of 22 metals and cognition status in older adults aged 60 years and above. A cross-sectional survey was conducted between 2018 and 2019. Inductively coupled plasma mass spectrometry (ICP-MS) was used to detect the concentrations of metals, and a mini-mental state examination (MMSE) questionnaire was used to estimate the cognition status of the elderly. Based on the years of education and MMSE scores, the participants were separated into the normal and impaired cognition groups. Lasso regression, logistic regression, and restricted cubic spline models were used to explore the relationship between the metals and cognitive status. A total of 1667 subjects were included in the study, and 333 (19.97%) of the participants had impaired cognition. Then, 12 metals, including Al, Fe, Ni, Cu, As, Se, Rb, Sr, Mo, Cd, Sn, and Sb were selected by lasso regression. Before the multivariate adjustment, Al and Cu were associated with the risk of increasing cognitive impairment (OR = 1.756, 95% CI: 1.166-2.646, P = 0.007; OR = 1.519, 95% CI: 1.050-2.197, P = 0.026, respectively). By contrast, Rb was associated with a decrease in the risk of cognitive impairment (OR = 0.626, 95% CI: 0.427-0.918, P = 0.017), but Cd was significantly associated with an increase in this risk (OR = 1.456, 95% CI: 1.003-2.114, P = 0.048). After multivariate adjustment, only Al (OR = 1.533, 95% CI: 1.000-2.350, P = 0.050) maintained a borderline difference with the risk of cognitive impairment. A significant positive correlation was found between the risk of cognitive impairment and Al, Cu, and Cd, contrary to the negative correlation found with Rb.

Associations between multiple heavy metals exposure and glycated hemoglobin in a Chinese population.

BACKGROUND: Heavy metals may play an important role as environmental risk factors in diabetes mellitus. This study aimed to explore the association of HbA1c with As, Cd, Cu, Ni, Pb, and Zn in single-metal exposure and multi-metal co-exposure models. METHODS: A cross-sectional study involving 3472 participants was conducted. Plasma concentrations of heavy metals were determined by inductively coupled plasma mass spectrometry. We estimated the association of each metal with HbA1c by linear regression. Potential heterogeneities by sex, age, and smoking were investigated, and metal mixtures and interactions were assessed by the Bayesian kernel machine regression (BKMR). RESULTS: In linear regression, Cu (ß = 0.324, p < 0.05) and Ni (ß = -0.19, p < 0.05) showed significant association with HbA1c in all participants. In BKMR analyses, all exposure-response relationships were approximately linear. Cu was significantly and positively associated with HbA1c levels in overall participants, women, participants aged 60 years old and above, and nonsmokers. Ni was significantly and negatively associated with HbA1c levels in overall participants. We did not observe the overall effect of plasma metal mixtures on HbA1c or the interaction effect of the metals on HbA1c. CONCLUSION: Cu was positively correlated with HbA1c, whereas Ni was negatively correlated with HbA1c, when evaluated individually or in a metal mixture. Additional studies are necessary to confirm these correlations and to control for exposure to different metals in the general population.

Associations of TFEB Gene Polymorphisms With Cognitive Function in Rural Chinese Population.

Background: The study aimed to investigate the relationship between transcription factor EB (TFEB) gene polymorphisms, including their haplotypes, and the cognitive functions of a selected population in Gongcheng County, Guangxi. Methods: A case-control study approach was used. The case group comprised 339 individuals with cognitive impairment, as assessed by their Mini-Mental State Examination scores; the control population also comprised 339 individuals who were matched by sex and age (± 5 years) in a 1:1 ratio. TFEB gene polymorphisms were genotyped in 678 participants (190 men and 488 women, aged 30-91 years) by using the Sequenom MassARRAY platform. Results: Multifactorial logistic regression analysis showed that in the dominant model, the risk of developing cognitive impairment was 1.547 times higher in cases with the TFEB rs14063A allele (AG + AA) than in those with the GG genotype (adjusted odds ratio [OR] = 1.547, Bonferroni correction confidence interval = 1.021-2.345). Meanwhile, the presence of the TFEB rs1062966T allele (CT + TT) was associated with a lower risk of cognitive impairment in comparison with the presence of the CC genotype (adjusted OR = 0.636, Bonferroni correction confidence interval = 0.405-0.998). In the co-dominant model, the risk of developing cognitive impairment was 1.553 times higher in carriers of the TFEB rs14063AG genotype than in carriers of the GG genotype (adjusted OR = 1.553, Bonferroni correction confidence interval = 1.007-2.397). After the Bonferroni correction and adjustment for confounding factors, the association of TFEB rs1062966 with cognitive function persisted in the analyses stratified by education level. Ethnically stratified analysis showed a significant association between TFEB rs1062966 and cognitive function in the Yao population. The multilocus linkage disequilibrium analysis indicated that the identified single nucleotide polymorphisms were not inherited independently. The haplotype analysis suggested that the rs14063A-rs1062966C-rs2278068C-rs1015149T haplotype of the TFEB gene increased the risk of cognitive impairment (P < 0.05) and that the rs14063G-rs1062966T-rs2278068C-rs1015149C haplotype was associated with a reduced risk of cognitive impairment (P < 0.05). Conclusion: TFEB rs1062966 polymorphisms and their rs14063A-rs1062966C-rs2278068C-rs1015149T and rs14063G-rs1062966T-rs2278068C-rs1015149C haplotypes are genetic factors that may affect cognitive function among the rural Chinese population.

Correlation between urinary contents of some metals and fasting plasma glucose levels: A cross-sectional study in China.

Many metals are involved in the pathogenesis of diabetes, but most of existing studies focused on single metals. The study of mixtures represents real-life exposure scenarios and deserves attention. This study aimed to explore the potential relationship of urinary copper (Cu), zinc (Zn), arsenic (As), selenium (Se), and strontium (Sr) contents with fasting plasma glucose (FPG) levels in 2766 participants. The levels of metals in urine were determined by inductively coupled plasma-mass spectrometry. We used linear regression models and the Bayesian kernel machine regression (BKMR) to evaluate the association between metals and FPG levels. In the multiple metals linear regression, Zn (ß = 0.434), Se (ß = 0.172), and Sr (ß = -0.143) showed significant association with FPG levels (all P < 0.05). The BKMR model analysis showed that the results of single metal association were consistent with the multiple metals linear regression. The mixture of five metals had a positive over-all effect on FPG levels, and Zn (PIP = 1.000) contributed the most to the FPG levels. Cu and As were negatively correlated with FPG levels in women. The potential interaction effect between Cu and Sr was observed in participants aged ≥ 60 years old (Pinteraction = 0.035). In summary, our results suggested that multiple metals in urine are associated with FPG levels. Further studies are needed to confirm these findings and clarify the underlying mechanisms.