Related Experiment Video
Updated: May 11, 2026
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Dynamic Triangulation of Resting-State Networks and CSF Metabolites Reveals Bidirectional Causal Pathways in Multiple
Junyu Chen1, Jianlin Li2, Liuxin Ran1
1Southwest Medical University, Luzhou, Sichuan, China.
Abstract:
Emotional disorders associated with multiple sclerosis (MS) are key drivers of disease progression. Recently, resting-state functional magnetic resonance imaging (rs-fMRI) and cerebrospinal fluid (CSF) metabolites have been found to play a crucial role in elucidating this process, but the causal relationship between them remains to be clarified. Exploring underlying mechanisms is critical for developing targeted therapies, especially combined multidimensional neuromodulation. This study employed bidirectional two-sample Mendelian randomization (MR) analysis to investigate the causal relationships between 191 rs-fMRI phenotypes and MS, while also exploring the mediating role of 338 CSF metabolites. Forward MR analysis revealed that enhanced functional connectivity in networks such as the saliency and visual networks (pheno56, pheno461, pheno624, pheno932, pheno1183) is related to an elevated risk of MS, whereas enhanced functional connectivity in the motor and attention networks (pheno2, pheno681, pheno705, pheno1322, pheno1696) is linked to a reduced risk of MS. Reverse MR analysis demonstrates that MS exhibits a positive correlation with four of these phenotypes (pheno74, pheno606, pheno767, and pheno1013), and a negative correlation with one phenotype (pheno286). Furthermore, five CSF metabolites-N-formylanthranilic acid, N6-methyllysine, succinimide, methyl glucopyranoside(alpha+beta), and hypoxanthine-were identified as key mediators in the MS process acting through resting-state brain functional networks. The study establishes causal rs-fMRI signatures affecting MS susceptibility and progression, and identifies critical CSF metabolites mediating MS effects via functional networks. These findings not only provide novel intervention targets for MS and related emotional disorders but also lay a theoretical foundation for the development of multidimensional therapeutic strategies leveraging neuromodulation techniques.
