Causal relationship among obesity and body fat distribution and epilepsy subtypes

Skin Microbiota, Circulating Metabolic Biomarker, Epilepsy: A Mendelian Randomization Analysis

Epilepsy is a neurological disorder characterized by recurrent, unprovoked seizures. Currently, the associations among skin microbiota, circulating metabolites, and epilepsy are still not well studied. In this study, we applied univariate and two-step Mendelian randomization analysis using single nucleotide polymorphisms as instrumental variables to analyze the possible associations. Five skin microbiota (asv022, asv008, bacillales, clostridiale, and micrococcaceae) and four circulating metabolites were found to be associated with epilepsy. Our results also showed that leucine level (p-value = 0.0487, OR = 1.067) and glutamine level (p-value = 0.0372, OR = 1.065) show a slight increased association with epilepsy, while phospholipids in medium LDL (p-value = 0.0302, OR = 0.9308) and ratio of saturated fatty acids (p-value = 0.0309, OR = 0.9017) appear to show a slight inverse correlation with epilepsy. In addition, the heterogeneity test and horizontal pleiotropy analysis indicated these results are robust in different situations. By mapping analysis, 54 genes were associated with at least two metabolites. By functional analysis, these genes were enriched in the immune-related pathways, which may have systemic effects on brain function. Our results provide a novel insight for understanding possible mechanisms of some epilepsy associations, which by further study might provide avenues for therapy research.

Genetic associations between ULK3 and epilepsy: a two-sample Mendelian randomization study

Background and objectives

Observational studies have suggested that a multitude of pathological processes and biomolecules are involved in the initiation and development of epilepsy, and ULK3 is linked to the nervous system. However, it remains uncertain whether this association between ULK3 and epilepsy is causal and the direction of any causal relationship. This study employs a two-sample Mendelian randomization (MR) method to investigate the relationship between ULK3 and the risk of epilepsy.

Methods

We analyzed genome-wide association study (GWAS) summary statistics for ULK3 (sample size = 3,301), focal epilepsy (sample size = 39,348), and generalized epilepsy (sample size = 33,446). Bidirectional MR analyses were conducted to explore these relationships. We selected a set of single nucleotide polymorphisms (SNPs) with an association threshold of less than 1 × 10-5 as instrumental variables for further analysis. Various MR methods, including Inverse Variance Weighted, Weighted Median, MR-Egger Regression, Simple Model, Weighted Model, and Robust Adjustment Profile Score were used. Sensitivity analyses were performed to ensure the robustness of the results.

Results

Our MR analyses revealed a causal relationship where an increased level of ULK3 was associated with a decreased risk of focal epilepsy (odds ratio = 0.92, 95% confidence interval: 0.86-1.00, p = 0.041). No significant heterogeneity (Q = 7.85, p = 0.165) or horizontal pleiotropy (Egger regression intercept = 0.0191, p = 0.415) was detected. However, in the reverse analysis, we found no significant causal effect of focal epilepsy on ULK3 (p > 0.05). Furthermore, no significant causation was identified between ULK3 and generalized epilepsy (p > 0.05).

Conclusion

This study suggests a causal relationship between ULK3 and the risk of focal epilepsy from a genetic perspective. Nevertheless, further investigation is needed to understand the role of ULK3 in epilepsy fully.

The relationships between obesity and epilepsy: A systematic review with meta-analysis

OBJECTIVE

There is ongoing debate regarding the association between epilepsy and obesity. Thus, the aim of this study was to examine the correlation between epilepsy and obesity.

METHOD

This study adhered to the PRISMA guidelines for systematic reviews and meta-analyses. On The Prospero website, this study has been successfully registered (CRD42023439530), searching electronic databases from the Cochr-ane Library, PubMed, Web of Sciences and Embase until February 10, 2024.The search keywords included "Epilepsy", "Obesity", "Case-Control Studies", "cohort studies", "Randomized Controlled Trial" and "Cross-Sectional Studies". The medical subject headings(MeSH) of PubMed was utilized to search for relevant subject words and free words, and a comprehensive search strategy was developed. Two reviewers conducted article screening, data extraction and bias risk assessment in strict accordance with the predefined criteria for including and excluding studies. The predefined inclusion criteria were as follows: 1) Inclusion of case-control, cohort, randomized controlled trial, and cross-sectional studies; 2) Segregation of subjects into epileptic patients and healthy controls; 3)Obesity as the outcome measure; 4) Availability of comprehensive data; 5) Publication in English. The exclusion criteria were as follows: 1) Exclusion of animal experiments, reviews, and other types of studies; 2) Absence of a healthy control group; 3) Incomplete data; 4) Unextractable or unconvertible data; 5) Low quality, indicated by an Agency for Healthcare Research and Quality(AHRQ) score of 5 or lower,or a Newcastle-Ottawa Scale (NOS) score less than 3. The subjects included in the study included adults and children, and the diagnostic criteria for obesity were used at different ages. In this study, obesity was defined as having a body mass index(BMI) of 25 kg/m2 or higher in adults and being above the 85th percentile of BMI for age in children. We used obesity as an outcome measure for meta-analysis using RevMan, version 5.3.

RESULTS

A meta-analysis was conducted on a total of 17 clinical studies, which involved 5329 patients with epilepsy and 480837 healthy controls. These studies were selected from a pool of 1497 articles obtained from four electronic databases mentioned earlier. Duplicate studies were removed based on the search strategies employed. No significant heterogeneity was observed in the outcome measure of obesity in epileptic patients compared with healthy controls(p = 0.01,I2 = 49%). Therefore, a fixed effects model was utilized in this study. The findings revealed a significant difference in obesity prevalence between patients with epilepsy and healthy controls(OR = 1.28, 95%CI: 1.20-1.38, p<0.01).

CONCLUSION

The results of this meta-analysis indicate that epilepsy patients are more prone to obesity than healthy people, so we need to pay attention to the problem of post-epilepsy obesity clinically. Currently, there is a scarcity of largescale prospective studies. Additional clinical investigations are warranted to delve deeper into whether obesity is a comorbidity of epilepsy and whether obesity can potentially trigger epilepsy.

Genetic causal role of body mass index in multiple neurological diseases

Body mass index (BMI) is a crucial health indicator for obesity. With the progression of socio-economic status and alterations in lifestyle, an increasing number of global populations are at risk of obesity. Given the complexity and severity of neurological diseases, early identification of risk factors is vital for the diagnosis and prognosis of such diseases. In this study, we employed Mendelian randomization (MR) analysis utilizing the most comprehensive genome-wide association study (GWAS) data to date. We selected single nucleotide polymorphisms (SNPs) that are unaffected by confounding factors and reverse causality as instrumental variables. These variables were used to evaluate the genetic and causal relationships between Body Mass Index (BMI) and various neurological diseases, including Parkinson's Disease (PD), Alzheimer's Disease (AD), Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), Ischemic Stroke (IS), and Epilepsy (EP). The Inverse Variance Weighted (IVW) analysis indicated that there was no significant causal relationship between Body Mass Index (BMI) indicators and PD (P-value = 0.511), AD (P-value = 0.076), ALS (P-value = 0.641), EP (P-value = 0.380). However, a causal relationship was found between BMI indicators and MS (P-value = 0.035), and IS (P-value = 0.000), with the BMI index positively correlated with the risk of both diseases. The Cochran's Q test for MR-IVW showed no heterogeneity in the MR analysis results between the BMI index and the neurological diseases (P > 0.05). The Egger intercept test for pleiotropy revealed no horizontal pleiotropy detected in any of the neurological diseases studied (P > 0.05). It was found that there was no causal relationship between BMI and PD, AD, ALS, EP, and a genetic causal association with MS, and IS. Meanwhile, the increase in BMI can lead to a higher risk of MS and IS, which reveals the critical role of obesity as a risk factor for specific neurological diseases in the pathogenesis of the diseases.

Mendelian randomization study shows a causal effect of asthma on epilepsy risk

Objective

The relationship between asthma and epilepsy in observational studies is controversial. The purpose of this Mendelian randomization (MR) study is to investigate whether asthma causally contributes to epilepsy susceptibility.

Methods

Independent genetic variants strongly (P<5E-08) associated with asthma were from a recent meta-analysis of genome-wide association studies on 408,442 participants. Two independent summary statistics of epilepsy obtained from the International League Against Epilepsy Consortium (ILAEC, Ncases=15,212, and Ncontrols=29,677) and FinnGen Consortium (Ncases=6,260 and Ncontrols=176,107) were used in the discovery and replication stage, respectively. Several sensitivity analyses and heterogeneity analyses were further conducted to assess the stability of the estimates.

Results

Using the inverse-variance weighted approach, genetic predisposition to asthma was associated with an elevated risk of epilepsy in the discovery stage (ILAEC: odds ratio [OR]=1.112, 95% confidence intervals [CI]= 1.023-1.209, P = 0.012), but not verified in the replication stage (FinnGen: OR=1.021, 95%CI= 0.896-1.163, P =0.753). However, a further meta-analysis of both ILAEC and FinnGen showed a similar result (OR=1.085, 95% CI: 1.012-1.164, P = 0.022). There were no causal associations between the age onset of asthma and epilepsy. Sensitivity analyses yielded consistent causal estimates.

Conclusion

The present MR study suggests that asthma is associated with an increased risk of epilepsy independent of the age onset of asthma. Further studies are warranted to explain the underlying mechanisms of this association.