Introduction
Epilepsy is one of the complex and ever-present chronic diseases of neurology, pathologically characterized by sudden, abnormal electrical discharges that can lead to transient cerebral dysfunction [
1]. A body of epidemiological investigations suggested that the incidence rate was 61.44 per 100,000 person-years on a global scale [
2]. As estimated, epilepsy accounts for more than 0.5% of the global burden of disease, which has a substantial financial impact in terms of healthcare needs, premature death, and lost work productivity [
3]. In this context, early identification and prevention of epilepsy is a high priority.
Given the possibility to take snapshots of the intricate and multivariate biochemical processes involved in illness development, investigating the relationships between metabolic abnormalities and human diseases has sparked a great deal of interest [
4]. Likewise, there is a lot of research into the potential link between metabolites and epilepsy, implying that certain metabolites are involved in the development of epilepsy. Myo-inositol, for instance, has been shown in experimental experiments to have a seizure-suppressing impact, indicating a potential protective role for myo-inositol in epilepsy [
5,
6,
7]. In addition, the term "metabolic epilepsy" has been proposed by the International League Against Epilepsy (ILAE) organization, which has identified numerous metabolic issues in relation to epilepsy [
8]. Lin Lin Lee et al. [
9] also summarized 14 metabolic disorders involved in epilepsy, like urea cycle disorders [
10], glutaric aciduria [
11], and so on. However, to our knowledge, there is still a paucity of comprehensive and systematic research appraising the causal effect of blood metabolites on epilepsy. Hence, owing to the inherent defects of the conventional observational studies, it is unable to conclusively delineate a metabolite spectrum contributing to the development of epilepsy based on the existing evidence.
Mendelian randomization (MR), a recently developed analytic method, has been widely applied to infer causal impacts from exposures to outcomes [
12]. In the case of the absence of randomized controlled trials (RCTs) or embarking on new RCTs, the MR approach is a critical alternative strategy providing reliable evidence on the causality between exposures and disease risks [
13]. Specifically, MR design leverages single nucleotide polymorphisms (SNPs) as the unconfounded instrumental variables (IVs) to proxy the phenotypes of interest. Considering the random allocation of genetic variants during fertilization, in which the process mimics an RCT, confounding (like sex and age) is less likely to bias the causal inference [
14]. Besides, genotype formation happens before disease onset and is typically not affected by disease progression, thus making reverse causality less likely.
Given that the causal impacts of blood metabolites on epilepsy were poorly understood, this study utilized genome-wide association study (GWAS) statistics to systematically evaluate the potential causalities in a two-sample MR framework. To be more exploratory in identifying the prospective candidate metabolites implicated in the etiology of epilepsy, an exposure-wide design incorporating more than 400 blood metabolites was used in the present study. Findings from this work would not only help to realize the pathophysiology underlying epilepsy, but also provide reliable evidence for establishing feasible strategies for epilepsy screening and prevention in clinical practice.
Discussion
The current study suggested that genetic liability for higher levels of blood uridine and 2-hydroxystearate were causally associated with an increased risk of epilepsy, whereas genetic predisposition towards higher levels of decanoylcarnitine and myo-inositol played a protective role in epilepsy development. To the best of our knowledge, this is the first MR study to systematically appraise the causal role of human blood metabolites in the issue of epilepsy.
The high prevalence and recurrence of epilepsy have contributed to a heavy burden on human society, thus making disease screening and prevention extremely critical. Though some risk factors for epilepsy have been proposed, like brain infection or injury [
36], the etiology of epilepsy remains unclear in nearly half of the cases [
37]. Previous studies have reported several circulating biomarkers in preclinical epilepsy models [,
38,
39]. For instance, Wang et al. reported that blood matrix metalloproteinase-3 was reduced in patients with epilepsy compared with healthy controls [
40]. Although that existing literature has strongly connoted the involvement of metabolic disturbance in epilepsy, current evidence is unable to conclusively determine a causal role of circulating metabolites in epilepsy development. Inspired by the metabolites GWAS analysis conducted by Shin et al. [
17], we designed this exposure-wide MR study to systematically evaluate the causality between blood metabolites and epilepsy, expecting to decipher the metabolic coding underlying the epilepsy pathogenesis and provide more novel targets for epilepsy identification and prevention.
Our study suggested that genetic liability for an increased level of blood uridine and 2-hydroxystearate played a detrimental effect on epilepsy development. Few studies focused on the role of circulating uridine in the issue of epilepsy. Some observational studies reported that uridine might play a protective role in epilepsy [
41], whereas some studies found no effects of uridine on epilepsy incidence [
42]. These equivocal results were limited by methodological defects, like residual confounding. By leveraging MR, which is free from reverse causality and residual confounding, we found that higher levels of blood uridine predicted an increased risk of epilepsy. Previously, Slézia et al. reported an increased level of extracellular uridine in a rat model of aminopyridine-induced epilepsy, suggesting that uridine might participate in epilepsy-related neuronal activity changes [
42]. However, due to the gaps in the knowledge on the biofunction of uridine, future studies are warranted to investigate the underlying mechanisms. For 2-hydroxystearate, very limited investigations have reported its association with epilepsy. A previous study reported that 2-hydroxystearate was overexpressed in diabetes patients and was positively associated with glucose levels [
43]. Given that diabetes might induce epilepsy, there might be the possibility that 2-hydroxystearate causes epilepsy through diabetes, which warrants further exploration in specific experimental conditions.
Two metabolites, decanoylcarnitine, and myo-inositol, were suggested to have protective effects on epilepsy. Similarly, the literature about the role of decanoylcarnitine in epilepsy is extremely limited. Previously analysis reported the gluconeogenesis-inhibition effect of decanoylcarnitine, suggesting decanoylcarnitine might prevent epilepsy by regulating glucose metabolism [
44]. However, more details for the underlying mechanisms should be explored in further study. The protective impact of myo-inositol on epilepsy identified by this MR study was supported by a great deal of literature. Using electrophysiological method, Gamkrelidze et al. found that myo-inositol has a significant local seizure-suppressant effect [
5]. In a recent study, several favorable effects of myo-inositol were observed in rat models, including decreasing the frequency and duration of electrographic spontaneous recurrent seizures in the hippocampus, ameliorating epileptogenesis-related spatial learning and memory deficit, and alleviating cell loss in the hippocampus [
7]. Phosphoinositide signaling pathway and myo-inositol action on gamma amino butyric acid-A receptors were the possible mechanisms of this protective effect [,
45,
46].
Taken together, the findings of our study are partially in line with those of previous studies. Based on the existing literature, the preventive role of myo-inositol in epilepsy observed in experimental studies has been well-documented. By leveraging GWAS data, our MR analysis also supported that myo-inositol exerted a protective effect on epilepsy incidence. For uridine, previous analyses yielded discrepant results, which could be attributable to the methodological flaws of the traditional observational design. Our study showed that uridine had a negative impact on epilepsy risk using the MR design, which is largely free from reverse causality and residual confounding. Furthermore, in our investigation, 2-hydroxystearate and decanoylcarnitine were discovered to be possible metabolites involved in the etiology of epilepsy. Previously, research about the role of these two metabolites in the risk of epilepsy was extremely limited. Future functional analyses were warranted to further confirm their biological effects on the development of epilepsy.
In the present study, two blood metabolites, including threonate and 2-palmitoylglycerophosphocholine, were identified as the risk factors for epilepsy using GWAS data from the ILAE consortium. However, replication analysis using epilepsy GWAS data from the FinnGen consortium yielded discrepant estimates, which might be attributed to the small proportion of epilepsy cases in the FinnGen study (~ 3.32%). Owing to the discordant results derived from two independent datasets, conclusive interpretation for the role of threonate and 2-palmitoylglycerophosphocholine in the genesis of epilepsy could not be established.
The current study has several strengths. First, the major strength worth noting in this MR study is the wide range of blood metabolites we covered. Briefly, totally 482 metabolites were included for MR analysis, which is the most comprehensive and systematic study to investigate the metabolic profiles contributing to epilepsy to date. Second, using MR design, our study is largely free from reverse causation and residual confounding. Specifically, an array of methods was implemented to verify any violation of the MR assumptions to ensure the reliability of the MR estimates. Concordant directions and similar magnitude across various MR models confirmed the robustness of the MR estimates. No evidence of horizontal pleiotropy was detected using complementary statistical methods. Third, replication and meta-analyses were applied to further support the causal effects of certain metabolites on epilepsy. Even though estimates derived from the FinnGen consortium in replication analysis were not statistically significant, the consistent directions of the effect estimates were reassuring as they appeared not to occur by chance alone. Further meta-analysis revealed several metabolites remained a significant impact on epilepsy.
Several limitations should be noted in our study. First, owing to the limited number of SNPs reaching genome-wide significance, we relaxed the P threshold, which is a common method widely used. The F statistic for each of the SNPs was over 10, suggesting no weak instruments were included. Besides, the Steiger test indicated a valid causal direction from the exposure to the outcome. As known, the rationale for the Steiger test is to compare the proportion of variance explained by the exposure-SNPs with that of the outcome-SNPs. Hence, the true direction derived from the Steiger test also supported the validity of the SNPs with relaxed P values. Second, the majority of the participants of this study are European. While this could largely avoid population heterogeneity, the MR results should be further validated in other populations to verify the generality in future studies when more GWAS data from other populations were publicly available. Third, despite the investigation of more than 400 blood metabolites, MR estimations were not adjusted for multiple testing in the present study. Instead, we conducted a replication analysis to verify the robustness of the MR estimates using two independent datasets (ILAE and FinnGen), greatly enhancing the credibility of our results. We argue that a conservative threshold of multiple testing might obscure the associations that were potentially noteworthy when studied alone. As such, potential candidate metabolites associated with epilepsy at P < 0.05 were included for further replication and meta-analyses in the present study. Finally, although that the MR approach performs excellently in causal inference, we caution that findings from this MR study should be further validated in well-powered randomized controlled trials to demonstrate the existence of causality.
In conclusion, this MR study suggests that blood metabolites might influence the risk of epilepsy in a causal way, initially providing evidence about the impact of circulating metabolic disturbance on epilepsy risk. Specifically, blood uridine, 2-hydroxystearate, decanoylcarnitine, and myo-inositol might be useful circulating metabolic biomarkers for epilepsy screening and prevention in clinical practice. These four metabolites can also serve as candidate molecules for future mechanism exploration.
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