Mutations in the SPAST gene causing hereditary spastic paraplegia are related to global topological alterations in brain functional networks

Abstract

Aim: Our aim was to describe the rearrangements of the brain activity related to genetic mutations in the SPAST gene.

Methods: Ten SPG4 patients and ten controls underwent a 5 min resting state magnetoencephalography recording and neurological examination. A beamformer algorithm reconstructed the activity of 90 brain areas. The phase lag index was used to estimate synchrony between brain areas. The minimum spanning tree was used to estimate topological metrics such as the leaf fraction (a measure of network integration) and the degree divergence (a measure of the resilience of the network against pathological events). The betweenness centrality (a measure to estimate the centrality of the brain areas) was used to estimate the centrality of each brain area.

Results: Our results showed topological rearrangements in the beta band. Specifically, the degree divergence was lower in patients as compared to controls and this parameter related to clinical disability. No differences appeared in leaf fraction nor in betweenness centrality.

Conclusion: Mutations in the SPAST gene are related to a reorganization of the brain topology.

Keywords: Brain network; Hereditary spastic paraplegia; Magnetic source imaging; Magnetoencephalography; Motoneuron disease; Neural synchronization.

Fig. 1

Data analysis pipeline. a Raw MEG signals recorded by 154 sensors (a subset displayed here). b–d Respectively noisy channel, cardiac artifact, blinking artifact, removed during pre-processing phase. e MEG signals after artifact removal and noise cleaning. f Co-registration between MEG signals and MRI template. g Source reconstruction (beamforming). h Functional connectivity matrix estimated for each frequency band (delta, theta, alpha, beta, gamma) using the PLI. Rows and columns are the regions of interest, while the entries are the estimated values of the PLI. i Brain topology representation based on the MST

Fig. 2

Changes in global parameters. Differences of the degree divergence (K) in the beta band between SPG4 patients (SPG4) and controls (HS)

Fig. 3

Pearson coefficient correlation between degree divergence (K) and SPRS rate. Pearson coefficient correlation between the values at Spastic Paraplegia Rating Scale and the degree divergence (K) in eight SPG4 patients. Two subjects have the same values for degree divergence and for SPRS, so in the figure, they are superimposed. Two outliers have been excluded from the analysis