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The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment

Abstract : Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to assess subject-specific connectivity features within a given population (healthy or diseased). Here, we applied the Clinical Connectome Fingerprint (CCF) analysis to source-reconstructed magnetoencephalography (MEG) signals in a cohort of seventy-eight subjects: thirty-nine ALS patients and thirty-nine healthy controls. We set out to develop an identifiability matrix to assess the extent to which each patient was recognisable based on his/her connectome, as compared to healthy controls. The analysis was performed in the five canonical frequency bands. Then, we built a multilinear regression model to test the ability of the "clinical fingerprint" to predict the clinical evolution of the disease, as assessed by the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-r), the King's disease staging system, and the Milano-Torino Staging (MiToS) disease staging system. We found a drop in the identifiability of patients in the alpha band compared to the healthy controls. Furthermore, the "clinical fingerprint" was predictive of the ALSFRS-r (p = 0.0397; β = 32.8), the King's (p = 0.0001; β = − 7.40), and the MiToS (p = 0.0025; β = − 4.9) scores. Accordingly, it negatively correlated with the King's (Spearman's rho =-0.6041, p = 0.0003) and MiToS scales (Spearman's rho = − 0.4953, p = 0.0040). Our results demonstrated the ability of the CCF approach to predict the individual motor impairment in patients affected by ALS. Given the subject-specificity of our approach, we hope to further exploit it to improve disease management.
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https://hal.archives-ouvertes.fr/hal-03786854
Contributor : Giovanna RAMOS Connect in order to contact the contributor
Submitted on : Friday, September 23, 2022 - 4:57:49 PM
Last modification on : Wednesday, November 30, 2022 - 4:14:07 PM

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Antonella Romano, Emahnuel Trosi Lopez, Marianna Liparoti, Arianna Polverino, Roberta Minino, et al.. The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment. Neuroimage-Clinical, 2022, 35, pp.103095. ⟨10.1016/j.nicl.2022.103095⟩. ⟨hal-03786854⟩

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