Obesity and epilepsy: The first step of a long road

Assessing the causal association between human blood metabolites and the risk of gout

BACKGROUND

The occurrence of gout is closely related to metabolism, but there is still a lack of evidence on the causal role of metabolites in promoting or preventing gout.

METHODS

We applied a two-sample Mendelian randomization (MR) analysis to assess the association between 486 serum metabolites and gout using genome-wide association study statistics. The inverse variance weighting method was used to generate the main results, while sensitivity analyses using MR-Egger, weighted median, Cochran's Q test, Egger intercept test, and leave-one-out analysis, were performed to assess the stability and reliability of the results. We also performed a metabolic pathway analysis to identify potential metabolic pathways.

RESULTS

After screening, 486 metabolites were retained for MR analysis. After screening by IVW and sensitivity analysis, 14 metabolites were identified with causal effect on gout (P < 0.05), among which hexadecanedioate was the most significant candidate metabolite associated with a lower risk of gout (IVW OR = 0.50; 95% CI = 0.38-0.67; P = 1.65 × 10-6 ). Metabolic pathway analysis identified one pathway that may be associated with the disease.

CONCLUSION

This MR study combining genomics with metabolomics provides a novel insight into the causal role of blood metabolites in the risk of gout, which implies that examination of certain blood metabolites would be a feasible strategy for screening populations with a higher risk of gout.

Causal relationship between telomere length and epilepsy: A bidirectional Mendelian randomization study

OBJECTIVE

Observational studies have suggested a link between telomere length (TL) and epilepsy, but the direction of the effect and whether it is causal or not is still being debated. The objective of this study was to investigate the causal relationship between TL and epilepsy using Mendelian randomization (MR) analysis.

METHODS

We performed a bidirectional two-sample MR analysis using pooled statistics from genome-wide association studies (GWAS) of TL and epilepsy. Additionally, we conducted a replication analysis using data from another GWAS study on epilepsy to validate our findings. The final results were analyzed using five MR methods, with the inverse-variance weighted (IVW) method as the primary outcome. We applied methods such as radial MR, MR pleiotropy residual and outlier test and MR Steiger filters to exclude outliers. Sensitivity analyses were also conducted to assess heterogeneity and pleiotropy.

RESULTS

Our analysis found no evidence of a causal relationship between epilepsy and TL (all p-values >0.05). The sensitivity analysis confirms the robustness of these results.

SIGNIFICANCE

In summary, our study contradicts existing observational reports by not finding any evidence to support a causal relationship between epilepsy and TL. Further research is necessary to determine the underlying mechanism behind the association observed in observational studies.

Roles of gut microbiome in epilepsy risk: A Mendelian randomization study

Background

Recent studies have suggested an association between gut microbiomes (GMs) and epilepsy. However, the GM taxa identified in different studies are variable. In addition, observational studies cannot indicate causality. Therefore, our study aimed to explore the causal association of GMs with epilepsy and identify the most influential GM taxa.

Methods

We conducted a Mendelian randomization (MR) study using summary statistics from genome-wide association studies (GWAS) of 211 GM taxa and epilepsy. The GWAS summary statistics for 211 GM taxa (from phylum to genus level) were generated by the MiBioGen consortium, while the FinnGen consortium provided the GWAS summary statistics for epilepsy. The primary analytical method to assess causality was the inverse-variance weighted (IVW) approach. To complement the IVW method, we also applied four additional MR methods: MR-Egger, weighted median, simple mode, and weighted. In addition, we conducted sensitivity analyses using Cochrane's Q-test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out analysis.

Results

We evaluated the causal effect of 211 GM taxa (from phylum to genus level) on epilepsy, generalized epilepsy, and focal epilepsy. After using the Bonferroni method for multiple testing correction, Class Betaproteobacteria [odds ratio (OR) = 1.357, 95% confidence interval (CI): 1.126-1.635, p = 0.001] and Order Burkholderiales (OR = 1.336, 95% CI: 1.112-1.606, p = 0.002). In addition, 21 nominally significant causal relationships were also identified. Further, the MR-Egger intercept test and MR-PRESSO global test suggested that our MR analysis was unaffected by horizontal pleiotropy (p > 0.05). Finally, the leave-one-out analysis suggested the robustness of the results.

Conclusion

Through the MR study, we analyzed the causal relationship of 211 GM taxa with epilepsy and determined the specific intestinal flora associated with increased epilepsy risk. Our findings may provide helpful biomarkers for disease progression and potential candidate therapeutic targets for epilepsy. In addition, in-depth analysis of large-scale microbiome GWAS datasets based on metagenomics sequencing is necessary for future studies.

Sex-related associations between body mass index and the incidence of epilepsy

BACKGROUND

The aim of this study was to investigate the association between both overweight and underweight and epilepsy in adult individuals using a large German database.

METHODS

This retrospective cohort study was based on data from the Disease Analyzer database (IQVIA) and included patients with documented body mass index (BMI) values followed up in one of 832 general practices in Germany between January 2006 and December 2019. The association between BMI categories and the 10-year incidence of epilepsy was studied separately for women and men using Cox regression models adjusted for age and comorbidities.

RESULTS

This study included 822,071 patients. The proportions of underweight, normal weight, overweight, and obesity were 1.6%, 33.4%, 36.7%, and 28.3% respectively. Underweight was significantly and positively associated with the incidence of epilepsy (HR = 1.67, 95% CI = 1.31-2.11) compared to normal weight. This association was much stronger in men (HR = 2.57, 95% CI = 1.71-3.88) than in women (HR = 1.48, 95% CI = 1.10-1.98). However, underweight was significantly associated with an increased risk of generalized epilepsy only (HR: 4.38; 95% CI: 1.34-14.35), but no significant associations between weight and the incidence of focal epilepsy was observed.

CONCLUSION

In conclusion, a significant and positive association between underweight and generalized and unclassified epilepsy was observed, which was stronger in men than in women. Further studies are needed to confirm these results and find the reasons for this association.

Assessing the causal association between human blood metabolites and the risk of epilepsy

Background

Metabolic disturbance has been reported in patients with epilepsy. Still, the evidence about the causal role of metabolites in facilitating or preventing epilepsy is lacking. Systematically investigating the causality between blood metabolites and epilepsy would help provide novel targets for epilepsy screening and prevention.

Methods

We conducted two-sample Mendelian randomization (MR) analysis. Data for 486 human blood metabolites came from a genome-wide association study (GWAS) comprising 7824 participants. GWAS data for epilepsy were obtained from the International League Against Epilepsy (ILAE) consortium for primary analysis and the FinnGen consortium for replication and meta-analysis. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy.

Results

482 out of 486 metabolites were included for MR analysis following rigorous genetic variants selection. After IVW and sensitivity analysis filtration, six metabolites with causal effects on epilepsy were identified from the ILAE consortium. Only four metabolites remained significant associations with epilepsy when combined with the FinnGen consortium [uridine: odds ratio (OR) = 2.34, 95% confidence interval (CI) = 1.48–3.71, P = 0.0003; 2-hydroxystearate: OR = 1.61, 95% CI = 1.19–2.18, P = 0.002; decanoylcarnitine: OR = 0.82, 95% CI = 0.72–0.94, P = 0.004; myo-inositol: OR = 0.77, 95% CI = 0.62–0.96, P = 0.02].

Conclusion

The evidence that the four metabolites mentioned above are associated with epilepsy in a causal way provides a novel insight into the underlying mechanisms of epilepsy by integrating genomics with metabolism, and has an implication for epilepsy screening and prevention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03648-5.