Disruption of the atrophy-based functional network in multiple sclerosis is associated with clinical disability: Validation of a meta-analytic model in resting-state functional MRI

Florence L. Chiang, Max Feng, Rebecca S. Romero, Larry Price, Crystal G. Franklin, Shengwen Deng, Jodie P. Gray, Fang F. Yu, Bundhit Tantiwongkosi, Susie Y. Huang, Peter T. Fox

Research output: Contribution to journalArticlepeer-review

Abstract

Background: In multiple sclerosis (MS), gray matter (GM) atrophy exhibits a specific pattern, which correlates strongly with clinical disability. However, the mechanism of regional specificity in GM atrophy remains largely unknown. Recently, the network degeneration hypothesis (NDH) was quantitatively defined (using coordinate-based meta-analysis) as the atrophy-based functional network (AFN) model, which posits that localized GM atrophy in MS is mediated by functional networks. Purpose: To test the NDH in MS in a data-driven manner using the AFN model to direct analyses in an independent test sample. Materials and Methods: Model fit testing was conducted with structural equation modeling, which is based on the computation of semipartial correlations. Model verification was performed in coordinate-based data of healthy control participants from the BrainMap database (https://www.brainmap.org). Model validation was conducted in prospectively acquired resting-state functional MRI in participants with relapsing-remitting MS who were recruited between September 2018 and January 2019. Correlation analyses of model fit indices and volumetric measures with Expanded Disability Status Scale (EDSS) scores and disease duration were performed. Results: Model verification of healthy control participants included 80 194 coordinates from 9035 experiments. Model verification in healthy control data resulted in excellent model fit (root mean square error of approximation, 0.037; 90% CI: 0.036, 0.039). Twenty participants (mean age, 36 years 6 9 [standard deviation]; 12 women) with relapsing-remitting MS were evaluated. Model validation in resting-state functional MRI in participants with MS resulted in deviation from optimal model fit (root mean square error of approximation, 0.071; 90% CI: 0.070, 0.072), which correlated with EDSS scores (r = 0.68; P = .002). Conclusion: The atrophy-based functional network model predicts functional network disruption in multiple sclerosis (MS), thereby supporting the network degeneration hypothesis. On resting-state functional MRI scans, reduced functional network integrity in participants with MS had a strong positive correlation with clinical disability.

Original languageEnglish (US)
Pages (from-to)159-166
Number of pages8
JournalRADIOLOGY
Volume299
Issue number1
DOIs
StatePublished - Apr 2021

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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