Causal Insights into the Metabolic Architecture of Multiple Sclerosis: Evidence from a Metabolome-Wide Mendelian Randomization Study
Multiple sclerosis (MS) is a chronic immune-mediated disorder of the central nervous system characterized by inflammation, demyelination, and neurodegeneration. Although numerous environmental, genetic, and lifestyle factors have been associated with MS risk, establishing causality has remained challenging due to confounding and reverse causation inherent in observational studies. Metabolomics has emerged as a powerful tool to identify circulating metabolites associated with MS; however, whether these metabolites play causal roles in disease pathogenesis has been unclear. The study by Ge et al. addresses this gap by applying a metabolome-wide Mendelian randomization (MR) framework to systematically prioritize circulating metabolites with likely causal effects on MS risk.
Rationale for a Metabolome-Wide Mendelian Randomization Approach
Mendelian randomization leverages the random allocation of genetic variants at conception to infer causal relationships between exposures and disease outcomes, thereby mimicking key aspects of randomized controlled trials. Previous MR studies in MS have focused on a limited set of exposures, such as body mass index, vitamin D levels, or lipid traits. In contrast, this work extends the MR paradigm to the entire circulating metabolome. By integrating large-scale genome-wide association studies (GWAS) of blood metabolites with a well-powered MS GWAS, the authors aimed to overcome biases of traditional metabolomics studies and provide a systematic causal map linking metabolic variation to MS susceptibility.
Data Sources and Instrument Selection Strategy
The authors combined summary statistics from three independent GWAS of circulating metabolites, collectively covering 571 metabolites measured in up to 115,078 individuals of European ancestry. Genetic associations with MS were obtained from the International Multiple Sclerosis Genetics Consortium, comprising 14,802 cases and 26,703 controls. Single nucleotide polymorphisms were selected as instrumental variables using both stringent (P < 5 × 10⁻⁸) and suggestive (P < 1 × 10⁻⁶) significance thresholds, ensuring adequate coverage of metabolites while maintaining instrument strength. Only metabolites with at least three independent genetic instruments were included, allowing for robust pleiotropy assessment and sensitivity analyses.
Statistical Framework and Robustness Analyses
The primary causal estimates were derived using a multiplicative random-effects inverse variance–weighted (IVW) method, which accounts for heterogeneity across genetic instruments. To assess robustness and detect potential violations of MR assumptions, the authors implemented multiple complementary methods, including MR-Egger, weighted median, weighted mode, MR-PRESSO, and MR Steiger directionality tests. This comprehensive analytical framework strengthens confidence in the inferred causal relationships by addressing horizontal pleiotropy, outlier effects, and reverse causation.
Key Findings: Lipids, Amino Acids, and Energy Metabolism
Across all analyses, 29 circulating metabolites showed evidence of causal association with MS risk. Notably, lipid-related metabolites exhibited subclass-specific effects. Genetically predicted higher levels of total cholesterol, phospholipids, and triglycerides in large very-low-density lipoproteins were associated with reduced MS risk, whereas the same lipid classes in very large high-density lipoproteins were linked to increased risk. Among amino acids, higher genetically determined levels of serine and lysine were associated with increased MS susceptibility. Additionally, metabolites involved in energy metabolism, particularly the ketone bodies acetoacetate and acetone, showed strong positive associations with MS risk, highlighting metabolic pathways beyond classical immune signaling.
Biological Interpretation and Pathophysiological Implications
The identified metabolites align with known metabolic disturbances observed in MS patients, lending biological plausibility to the MR findings. Alterations in lipid metabolism may influence myelin integrity, immune cell function, and neuroinflammatory processes, while amino acids such as serine and lysine are integral to one-carbon metabolism, neurotransmitter synthesis, and lipid biosynthesis. The causal association of ketone bodies suggests a complex role for energy metabolism in MS, potentially reflecting adaptive or maladaptive metabolic responses during disease development. Importantly, these results suggest that metabolic changes observed in MS are not merely consequences of disease but may actively contribute to its onset.
Strengths, Limitations, and Future Directions
This study represents the first comprehensive metabolome-wide MR analysis in MS, offering a systematic prioritization of candidate causal metabolites. Key strengths include the use of large GWAS datasets, multiple instrument selection thresholds, and extensive sensitivity analyses. Nevertheless, limitations remain, including residual pleiotropy, restriction to European ancestry, and the inability to distinguish MS subtypes or nonlinear exposure–outcome relationships. Future research should focus on validating these findings in diverse populations, exploring mechanistic pathways linking prioritized metabolites to neuroimmunology, and assessing whether these metabolites can serve as early biomarkers or therapeutic targets for MS prevention and intervention.
Disclaimer: This blog post is based on the provided research article and is intended for informational purposes only. It is not intended to provide medical advice. Please consult with a healthcare professional for any health concerns.
References:
Ge, A., Sun, Y., Kiker, T., Zhou, Y., & Ye, K. (2023). A metabolome-wide Mendelian randomization study prioritizes potential causal circulating metabolites for multiple sclerosis. Journal of neuroimmunology, 379, 578105.
