Metabolite Associations with Childhood and Juvenile Absence Epilepsy: A Bidirectional Mendelian Randomization Study
Jinwen Liu1, Ruoyu Li1, Haichun Yu2
1First School of Clinical Medicine, Guangxi University of Chinese Medicine, Nanning, China.
Background:
The precise involvement of metabolites in the pathogenesis of Childhood absence epilepsy (CAE) and juvenile absence epilepsy (JAE) remains elusive. Consequently, this investigation introduces bidirectional Mendelian randomization (MR) as a tool to explore causality and underlying mechanisms.
Methods:
Bidirectional MR analysis was conducted employing a comprehensive set comprising 1091 human blood metabolites and 309 metabolite ratios, systematically probing potential causal associations with JAE and CAE. Genome-wide association study (GWAS) data pertaining to these epileptic conditions were meticulously obtained from the International League Against Epilepsy (ILAE) consortium. Sensitivity analyses were rigorously performed to evaluate for heterogeneity and pleiotropy. Reverse MR analysis was also conducted to verify the direction of causality, and no significant reverse causal relationships were identified.
Results:
Following rigorous genetic variant selection, significant associations were identified based on PIVW < .05, PWM < .05, and PMR-Egger < .05 criteria in MR analysis. Only 1 metabolite, (2 or 3)-decaonate levels, exhibited an association with JAE (P = .005, OR=0.987, 95% CI=0.978-0.996). Childhood absence epilepsy was associated with 5 metabolites: X-23648 (P = .012, OR=0.982, 95% CI=0.968-0.996), X-21845 levels (P = .045, OR=1.018, 95% CI=1.001-1.035), 2'-o-methylcytidine (P = .008, OR=0.995, 95% CI=0.991-1.001), 2'-o-methyluridine (P = .007, OR=0.995, 95% CI=0.99-0.999), and spermidine-topyruvate ratio (P = .014, OR=0.973, 95% CI=0.954-0.992). No evidence of reverse causality was found between JAE and CAE and the aforementioned metabolites.
Conclusion:
The study establishes causal relationships between the aforementioned 6 metabolites and CAE and JAE. This integration of genomics with metabolism offers novel insights into epilepsy mechanisms and has important implications for screening and prevention.
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