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Background <p>Abnormalities in large-scale brain functional networks are implicated in multiple sclerosis (MS) and linked to clinical impairments, but reported findings remain heterogeneous due to methodological and sample variations.</p> Methods <p>Based on 25 resting-state functional magnetic resonance (rsfMRI) imaging studies (1,524 MS patients and 886 healthy controls (HCs)), in which the independent component analysis (ICA) method was used to evaluate the resting-state functional connectivity (rsFC) changes in default mode (DMN), sensorimotor (SMN), salience (SN), and visual (VN) networks, a meta-analysis was performed using the anisotropic effect size seed mapping (AES-SDM) software to quantify the differences between MS patients and HCs. The heterogeneity was assessed, and a meta-regression analysis was conducted on age, disease duration, Expanded Disability Status Scale scores, and T2-hyperintense lesion volume.</p> Results <p>Compared with HCs, MS exhibited increased rsFC in left anterior cingulate/paracingulate gyri and right superior frontal gyrus (DMN), bilateral precentral gyrus and right postcentral gyrus (SMN), right angular gyrus (SN), whereas hypoconnectivity was observed in left posterior cingulate gyrus (DMN), right supplementary motor region and left precentral gyrus (SMN), right insula (SN), and left superior parietal gyrus (VN). The Meta-regression analysis revealed no significant correlation between these altered rsFC and clinical variables.</p> Data conclusions <p>This study demonstrates widespread and complex rsFC abnormalities in several neural networks in MS, particularly within core regions of the DMN, SMN, VN, and SN. Together with a descriptive synthesis of additional RSNs, these rsFC disruptions and reorganizations may represent intrinsic neuropathological alterations in MS, which further elucidate the pathophysiological mechanisms of functional abnormalities in MS at a large-scale level.</p>

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Disrupted and reorganized connectivity of brain networks in multiple sclerosis: a systematic review and meta-analysis of resting-state functional MRI

  • 期刊论文

  • 发表日期：

    2026年2月11日

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  • Bingyi Qu,
  • Siyi Li,
  • Hongxi Chen,
  • Ying Zhang,
  • Su Lui,
  • Peilin Lv,
  • Li Yao

摘要

Background

Abnormalities in large-scale brain functional networks are implicated in multiple sclerosis (MS) and linked to clinical impairments, but reported findings remain heterogeneous due to methodological and sample variations.

Methods

Based on 25 resting-state functional magnetic resonance (rsfMRI) imaging studies (1,524 MS patients and 886 healthy controls (HCs)), in which the independent component analysis (ICA) method was used to evaluate the resting-state functional connectivity (rsFC) changes in default mode (DMN), sensorimotor (SMN), salience (SN), and visual (VN) networks, a meta-analysis was performed using the anisotropic effect size seed mapping (AES-SDM) software to quantify the differences between MS patients and HCs. The heterogeneity was assessed, and a meta-regression analysis was conducted on age, disease duration, Expanded Disability Status Scale scores, and T2-hyperintense lesion volume.

Results

Compared with HCs, MS exhibited increased rsFC in left anterior cingulate/paracingulate gyri and right superior frontal gyrus (DMN), bilateral precentral gyrus and right postcentral gyrus (SMN), right angular gyrus (SN), whereas hypoconnectivity was observed in left posterior cingulate gyrus (DMN), right supplementary motor region and left precentral gyrus (SMN), right insula (SN), and left superior parietal gyrus (VN). The Meta-regression analysis revealed no significant correlation between these altered rsFC and clinical variables.

Data conclusions

This study demonstrates widespread and complex rsFC abnormalities in several neural networks in MS, particularly within core regions of the DMN, SMN, VN, and SN. Together with a descriptive synthesis of additional RSNs, these rsFC disruptions and reorganizations may represent intrinsic neuropathological alterations in MS, which further elucidate the pathophysiological mechanisms of functional abnormalities in MS at a large-scale level.