The compensatory effect of brain functional connectivity enhancement in relapsing-remitting multiple sclerosis (RRMS) remains controversial.
Objective:
To characterize the relationships between brain functional connectivity changes and disability progression in RRMS.
Methods:
Long-range connectivity, short-range connectivity, and density of connections were assessed using graph theoretical analysis of resting-state functional magnetic resonance imaging (fMRI) data acquired in 38 RRMS patients (disease duration: 120 ± 32 months) and 24 controls. All subjects were explored at baseline and all patients and six controls 2 years later.
Results:
At baseline, levels of long-range and short-range brain functional connectivity were higher in patients compared to controls. During the follow-up, decrease in connections’ density was inversely correlated with disability progression. Post-hoc analysis evidenced differential evolution of brain functional connectivity metrics in patients according to their level of disability at baseline: while patients with lowest disability at baseline experienced an increase in all connectivity metrics during the follow-up, patients with higher disability at baseline showed a decrease in the connectivity metrics. In these patients, decrease in the connectivity metrics was associated with disability progression.
Conclusion:
The study provides two main findings: (1) brain functional connectivity enhancement decreases during the disease course after reaching a maximal level, and (2) decrease in brain functional connectivity enhancement participates in disability progression.
SchoonheimMMGeurtsJJGBarkhofF.The limits of functional reorganization in multiple sclerosis. Neurology2010; 74: 1246–1247.
2.
SumowskiJFRoccaMALeavittVM. Brain reserve and cognitive reserve protect against cognitive decline over 4.5 years in multiple sclerosis. Neurology2014; 82: 1776–1783.
3.
PantanoPMaineroCIannettiGD. Contribution of corticospinal tract damage to cortical motor reorganization after a single clinical attack of multiple sclerosis. Neuroimage2002; 17: 1837–1843.
4.
AudoinBAu DuongMVRanjevaJ-P. Magnetic resonance study of the influence of tissue damage and cortical reorganization on PASAT performance at the earliest stage of multiple sclerosis. Hum Brain Mapp2005; 24: 216–228.
5.
RoccaMAColomboBFaliniA. Cortical adaptation in patients with MS: A cross-sectional functional MRI study of disease phenotypes. Lancet Neurol2005; 4: 618–626.
6.
RicoAZaaraouiWFranquesJ. Motor cortical reorganization is present after a single attack of multiple sclerosis devoid of cortico-spinal dysfunction. MAGMA2011; 24: 77–84.
7.
LoitfelderMFazekasFPetrovicK. Reorganization in cognitive networks with progression of multiple sclerosis: Insights from fMRI. Neurology2011; 76: 526–533.
FilippiMvan den HeuvelMPFornitoA. Assessment of system dysfunction in the brain through MRI-based connectomics. Lancet Neurol2013; 12: 1189–1199.
10.
RoccaMAValsasinaPAbsintaM. Default-mode network dysfunction and cognitive impairment in progressive MS. Neurology2010; 74: 1252–1259.
11.
RoosendaalSDSchoonheimMMHulstHE. Resting state networks change in clinically isolated syndrome. Brain2010; 133: 1612–1621.
12.
BonavitaSGalloASaccoR. Distributed changes in default-mode resting-state connectivity in multiple sclerosis. Mult Scler2011; 17: 411–422.
13.
HawellekDJHippJFLewisCM. Increased functional connectivity indicates the severity of cognitive impairment in multiple sclerosis. Proc Natl Acad Sci U S A2011; 108: 19066–19071.
14.
FaivreARicoAZaaraouiW. Assessing brain connectivity at rest is clinically relevant in early multiple sclerosis. Mult Scler2012; 18: 1251–1258.
15.
GalloAEspositoFSaccoR. Visual resting-state network in relapsing-remitting MS with and without previous optic neuritis. Neurology2012; 79: 1458–1465.
16.
LoitfelderMFilippiMRoccaM. Abnormalities of resting state functional connectivity are related to sustained attention deficits in MS. PLoS ONE2012; 7: e42862.
17.
Cruz-GómezAJVentura-CamposNBelenguerA. The link between resting-state functional connectivity and cognition in MS patients. Mult Scler2014; 20: 338–348.
18.
LouapreCPerlbargVGarcia-LorenzoD. Brain networks disconnection in early multiple sclerosis cognitive deficits: An anatomofunctional study. Hum Brain Mapp2014; 35: 4706–4717.
19.
TonaFPetsasNSbardellaE. Multiple sclerosis: Altered thalamic resting-state functional connectivity and its effect on cognitive function. Radiology2014; 271: 814–821.
20.
AchardSSalvadorRWhitcherB. A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. J Neurosci2006; 26: 63–72.
21.
HeYDagherAChenZ. Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load. Brain2009; 132: 3366–3379.
22.
ShuNLiuYLiK. Diffusion tensor tractography reveals disrupted topological efficiency in white matter structural networks in multiple sclerosis. Cereb Cortex2011; 21: 2565–2577.
23.
HardmeierMSchoonheimMMGeurtsJJG. Cognitive dysfunction in early multiple sclerosis: Altered centrality derived from resting-state functional connectivity using magneto-encephalography. PLoS ONE2012; 7: e42087.
24.
SchoonheimMMGeurtsJJGLandiD. Functional connectivity changes in multiple sclerosis patients: A graph analytical study of MEG resting state data. Hum Brain Mapp2013; 34: 52–61.
25.
Van SchependomJGielenJLatonJ. Graph theoretical analysis indicates cognitive impairment in MS stems from neural disconnection. Neuroimage Clin2014; 4: 403–410.
26.
GamboaOLTagliazucchiEvon WegnerF. Working memory performance of early MS patients correlates inversely with modularity increases in resting state functional connectivity networks. Neuroimage2014; 94: 385–395.
27.
RoccaMAValsasinaPMeaniA. Impaired functional integration in multiple sclerosis: A graph theory study. Brain Struct Funct. Epub ahead of print 26 September 2014. DOI: 10.1007/s00429-0896-4.
28.
PolmanCHReingoldSCBanwellB. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol2011; 69: 292–302.
29.
KurtzkeJF.Rating neurologic impairment in multiple sclerosis: An Expanded Disability Status Scale (EDSS). Neurology1983; 33: 1444–1452.
30.
CutterGRBaierMLRudickRA. Development of a multiple sclerosis functional composite as a clinical trial outcome measure. Brain1999; 122: 871–882.
31.
Tzourio-MazoyerNLandeauBPapathanassiouD. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage2002; 15: 273–289.
32.
BullmoreEFadiliJMaximV. Wavelets and functional magnetic resonance imaging of the human brain. Neuroimage2004; 23(Suppl. 1): S234–S249.
33.
PalvaJMPalvaS.Infra-slow fluctuations in electrophysiological recordings, blood-oxygenation-level-dependent signals, and psychophysical time series. Neuroimage2012; 62: 2201–2211.
34.
WhitcherBGuttorpPPercivalDB.Wavelet analysis of covariance with application to atmospheric time series. J Geophys Res2000; 105: 941–962.
35.
CordesDHaughtonVMArfanakisK. Mapping functionally related regions of brain with functional connectivity MR imaging. Am J Neuroradiol2000; 21: 1636–1644.
36.
GuyeMBettusGBartolomeiF. Graph theoretical analysis of structural and functional connectivity MRI in normal and pathological brain networks. MAGMA2010; 23: 409–421.
37.
HwangKHallquistMNLunaB.The development of hub architecture in the human functional brain network. Cereb Cortex2013; 23: 2380–2393.
38.
MaineroCPantanoPCaramiaF. Brain reorganization during attention and memory tasks in multiple sclerosis: Insights from functional MRI studies. J Neurol Sci2006; 245: 93–98.
39.
FilippiMRiccitelliGMattioliF. Multiple sclerosis: Effects of cognitive rehabilitation on structural and functional MR imaging measures – An explorative study. Radiology2012; 262: 932–940.
40.
ParisiLRoccaMAValsasinaP. Cognitive rehabilitation correlates with the functional connectivity of the anterior cingulate cortex in patients with multiple sclerosis. Brain Imaging Behav2014; 8: 387–393.
