Effects of Selenium on Chronic Kidney Disease: A Mendelian Randomization Study

Fu, Shaojie; Zhang, Li; Ma, Fuzhe; Xue, Shuai; Sun, Tao; Xu, Zhonggao

doi:10.3390/nu14214458

Cited by 31 publications

(13 citation statements)

References 81 publications

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“…As an essential trace element, the positive influence of Se supplementation on CKD pathogenesis reaffirms our results of this study ( 21 – 23 ). However, the association between Se and CKD remains contentious, as some studies have suggested that Se supplementation may be detrimental to CKD patients ( 24 , 25 ). Our study observed a significant correlation between plasma Rb and rapid decline in renal function.…”

Section: Discussionmentioning

confidence: 99%

Comparative mathematical modeling of causal association between metal exposure and development of chronic kidney disease

Wu,

Hou,

Qin

et al. 2024

Front. Endocrinol.

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BackgroundPrevious studies have identified several genetic and environmental risk factors for chronic kidney disease (CKD). However, little is known about the relationship between serum metals and CKD risk.MethodsWe investigated associations between serum metals levels and CKD risk among 100 medical examiners and 443 CKD patients in the medical center of the First Hospital Affiliated to China Medical University. Serum metal concentrations were measured using inductively coupled plasma mass spectrometry (ICP-MS). We analyzed factors influencing CKD, including abnormalities in Creatine and Cystatin C, using univariate and multiple analysis such as Lasso and Logistic regression. Metal levels among CKD patients at different stages were also explored. The study utilized machine learning and Bayesian Kernel Machine Regression (BKMR) to assess associations and predict CKD risk based on serum metals. A chained mediation model was applied to investigate how interventions with different heavy metals influence renal function indicators (creatinine and cystatin C) and their impact on diagnosing and treating renal impairment.ResultsSerum potassium (K), sodium (Na), and calcium (Ca) showed positive trends with CKD, while selenium (Se) and molybdenum (Mo) showed negative trends. Metal mixtures had a significant negative effect on CKD when concentrations were all from 30th to 45th percentiles compared to the median, but the opposite was observed for the 55th to 60th percentiles. For example, a change in serum K concentration from the 25th to the 75th percentile was associated with a significant increase in CKD risk of 5.15(1.77,8.53), 13.62(8.91,18.33) and 31.81(14.03,49.58) when other metals were fixed at the 25th, 50th and 75th percentiles, respectively.ConclusionsCumulative metal exposures, especially double-exposure to serum K and Se may impact CKD risk. Machine learning methods validated the external relevance of the metal factors. Our study highlights the importance of employing diverse methodologies to evaluate health effects of metal mixtures.

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Section: Discussionmentioning

confidence: 99%

Comparative mathematical modeling of causal association between metal exposure and development of chronic kidney disease

Wu,

Hou,

Qin

et al. 2024

Front. Endocrinol.

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“…The evidence from the IVW method was complemented with the MR-Egger, weighted mode, weighted median, and simple mode. The conclusion would be more credible, stable, and precise when the consequences of these methods were consistent ( 26 ). For the IVW test and MR-Egger model, Cochran’s Q test was conducted to assess heterogeneity ( 27 ).…”

Section: Methodsmentioning

confidence: 99%

Causal associations between dietary factors and colorectal cancer risk: a Mendelian randomization study

Zhang,

Wu,

Wang

et al. 2024

Front. Nutr.

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BackgroundPrevious epidemiological studies have found a link between colorectal cancer (CRC) and human dietary habits. However, the inherent limitations and inevitable confounding factors of the observational studies may lead to the inaccurate and doubtful results. The causality of dietary factors to CRC remains elusive.MethodsWe conducted two-sample Mendelian randomization (MR) analyses utilizing the data sets from the IEU Open GWAS project. The exposure datasets included alcoholic drinks per week, processed meat intake, beef intake, poultry intake, oily fish intake, non-oily fish intake, lamb/mutton intake, pork intake, cheese intake, bread intake, tea intake, coffee intake, cooked vegetable intake, cereal intake, fresh fruit intake, salad/raw vegetable intake, and dried fruit intake. In our MR analyses, the inverse variance weighted (IVW) method was employed as the primary analytical approach. The weighted median, MR-Egger, weighted mode, and simple mode were also applied to quality control. Heterogeneity and pleiotropic analyses were implemented to replenish the accuracy of the results.ResultsMR consequences revealed that alcoholic drinks per week [odds ratio (OR): 1.565, 95% confidence interval (CI): 1.068–2.293, p = 0.022], non-oily fish intake (OR: 0.286; 95% CI: 0.095–0.860; p = 0.026), fresh fruit intake (OR: 0.513; 95% CI: 0.273–0.964; p = 0.038), cereal intake (OR: 0.435; 95% CI: 0.253–0.476; p = 0.003) and dried fruit intake (OR: 0.522; 95% CI: 0.311–0.875; p = 0.014) was causally correlated with the risk of CRC. No other significant relationships were obtained. The sensitivity analyses proposed the absence of heterogeneity or pleiotropy, demonstrating the reliability of the MR results.ConclusionThis study indicated that alcoholic drinks were associated with an increased risk of CRC, while non-oily fish intake, fresh fruit intake, cereal intake, and dried fruit were associated with a decreased risk of CRC. This study also indicated that other dietary factors included in this research were not associated with CRC. The current study is the first to establish the link between comprehensive diet-related factors and CRC at the genetic level, offering novel clues for interpreting the genetic etiology of CRC and replenishing new perspectives for the clinical practice of gastrointestinal disease prevention.

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“…Fourthly, if the f-statistic exceeds 10, using the formula F = R 2 (N-K-1)/[K (1-R 2 )], the selected IV is selected, indicating strong predictive potential. [ 27 ] Finally, we extract SNPs related to COVID-19 from the result dataset and discard SNPs related to infertility ( P ≤1 × 10 -5 ). In addition, the SNP information in the resulting data is shown in Tables 2 and 3 .…”

Section: Methodsmentioning

confidence: 99%

The association between COVID-19 and infertility: Mendelian randomization analysis

Zhang,

Wen,

Wang

2024

Medicine

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Since December 2019, COVID-19 has triggered a global pandemic. The association of COVID-19 with the long-term reproductive situation of women and males is not clear. Thus, our aim was to assess the causal association between COVID-19 and infertility using Mendelian randomization (MR) analysis based on the OpenGWAS database. Two-sample MR analysis was conducted using one genome-wide association study (GWAS) on COVID-19 and infertility in individuals of European ancestry. The summary data of genetic variation come from the GWAS in European populations. We applied several MR methods, including MR Egger, weighted median, inverse variance weighted, simple mode, weighted mode, to test causal relationships. After observing the statistical analysis results of MR, we conducted sensitivity analysis to test robustness. After gene prediction, it was found that there was no clear causal relationship between COVID-19 and male infertility in MR analysis [OR 0.4702 (95% CI, 0.1569–1.4093), P = .178]. Moreover, COVID-19 was not associated with female infertility [OR 0.9981 (95% CI, 0.763–1.544), P = .646]. Sensitivity analysis showed that the MR results were robust [level pleiotropy, male: (MR–Egger, intercept = 0.1967434; se = 0.1186876; P = .2392406); female: (MR–Egger, intercept = −0.05902506; se = 0.05362049; P = .3211367)]. To further validate the impact of COVID-19 on infertility, we added a covariate (sex hormone binding global levels, abortion) to the MR analysis, which is a multivariate MR analysis. According to univariate and multivariate MR analyses, the evidence does not support that COVID-19 is a causal risk factor for infertility in European population. This information can provide information for doctors in reproductive centers when managing infertility patients.

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Effects of Selenium on Chronic Kidney Disease: A Mendelian Randomization Study

Cited by 31 publications

References 81 publications

Comparative mathematical modeling of causal association between metal exposure and development of chronic kidney disease

Comparative mathematical modeling of causal association between metal exposure and development of chronic kidney disease

Causal associations between dietary factors and colorectal cancer risk: a Mendelian randomization study

The association between COVID-19 and infertility: Mendelian randomization analysis

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