According to previous epidemiology studies, the neurotoxic effects of excess selenium exposure may contribute to ALS etiology [29, 30]. However, observational studies are prone to reverse causation and various confounders, in which case incorrect causal inference might be made even with careful study design and statistical adjustment [31–33]. Here we leveraged the summary statistics from recent large-scale GWAS datasets to probe the association between selenium exposure and the risk for ALS. The current evidence did not support any causal relationship between the two, which is in accordance with the null association found between ALS and erythrocyte-bound selenium level in a recent prospective case-control study . However, given the modest number of valid IVs available for this analysis and the relatively low percentage of variance in selenium level explained by these IVs, the statistical power to detect any postulated causal association might be limited. Therefore, until more genome-wide significant selenium variants are identified from future large scale GWAS studies, we cannot completely rule out the possibility that selenium exposure may influence the risk for ALS.
Since two-sample MR assumes that the SNPs influence the outcome because the hypothesized exposure does (vertical pleiotropy), three assumptions need to be satisfied for valid MR analysis: the genetic variants used as IVs are associated with the exposure (the relevance assumption); the genetic variants were not associated with any confounders (the independence assumption); and the genetic variants influence the risk of ALS only through the pathway of the exposure (the exclusion assumption) [20, 34]. Thus, to validate the IV assumptions, two alternative mechanisms need to be ruled out: IVs also being in LD with a causal variant for the outcome; IVs influencing the outcome through a pathway other than the exposure (horizontal pleiotropy) . After LD-based clumping and pruning, multiple independent genetic variants reaching the conventional genome-wide significance level (thereby validating the relevance assumption) were meta-analyzed via IVW for an overall estimate of their effect on the outcome in our study. However, although using multiple genetic variants can enhance the statistical power of MR analysis, the causal estimate would be liable to bias with inflated type I error rates if invalid IVs are included . Thus, no variant having potential pleiotropic associations with ALS (defined by an ALS association p value below the genome-wide suggestive significance level of 10− 5) was included as IV in the current MR analysis. Since the second and third IV assumptions are not fully testable in practice, we compared the estimates from a range of sensitivity analyses, which were in accordance with the IVW result.
Nonetheless, since metal homeostasis is critical for normal brain function, an excess of metal levels has been postulated as potential risk factors for a variety of neurodegenerative disorders . Accordantly, the concentration of trace metals in Alzheimer’s disease patients’ hair and nails were found related to the clinical course of the disease . It has been found that the concentration of selenium in urine and scalp hair was elevated in men, which is consistent with the epidemiologic findings that ALS is more common in men than in women [6, 38, 39]. The neurotoxic effects of selenium might be mediated by inducing oxidation of thiol-containing protein and promoting translocation of copper/zinc superoxide dismutase (SOD1) into mitochondria . However, the biomarkers currently used to assess selenium exposure have various inherent limitations, and the reliability of these assessment methods in reflecting the long-term cumulative exposure of selenium has been debated and challenged . In addition, peripheral indicators of selenium exposure may not necessarily correspond to its CNS content, given the independence of selenium level in paired serum and cerebrospinal fluid (CSF) samples . Thus, despite the negative results from the MR analysis, further functional studies investigating the association between selenium and ALS are still warranted.
The study is subject to a number of limitations. First, although there is evidence supporting the existence of variation in the concentration of metals/metalloids by age and gender , we cannot decide whether there is any age- or gender-specific effect of selenium exposure on ALS, as individual-level GWAS datasets are not accessible. Second, to avoid population stratification, we focused on subjects of European ethnicity. Whether the findings may be extended to other populations remains unclear. Finally, although the MR-Egger regression results did not support horizontal pleiotropy, it is difficult to completely rule out pleiotropy or alternative causal pathways in MR analyses. In addition, MR analysis assumed linearity and homogeneity between the exposure, the genetic variants, and the risk for ALS, which may not represent the true associations in nature. This could potentially limit us from identifying putative thresholds of exposure above or below which the exposure can induce specific effects.
In conclusion, using summary statistics from GWAS, we did not find strong evidence for the causal inference of selenium on the risk of ALS in the present study. Such findings might be informative for epidemiologic studies of ALS in the future.