Abnormal functional connectivity of thalamic sub-regions contributes to fatigue in multiple sclerosis

Abstract

Objective:

To investigate sub-regional thalamic resting-state (RS) functional connectivity (FC) abnormalities in multiple sclerosis (MS) and their correlation with fatigue and its subcomponents (physical, cognitive, and psychosocial).

Methods:

From 122 MS patients and 94 healthy controls, 5 thalamic sub-regions (frontal, motor, postcentral, occipital, temporal) were parcellated based on their cortico-thalamic structural connectivity and used for a seed-based RS FC analysis. Abnormalities of thalamic RS FC in MS patients and their correlation with Modified Fatigue Impact Scale (MFIS) were assessed.

Results:

Compared to controls and non-fatigued MS (n = 86), fatigued MS patients (n = 36) showed thalamic RS FC abnormalities with middle frontal gyrus, sensorimotor network, precuneus, insula, and cerebellum, which correlated with global MFIS. Higher thalamic RS FC with precuneus and lower RS FC with posterior cerebellum correlated with cognitive MFIS. Higher thalamic RS FC with sensorimotor network in frontal-, motor-, and temporal thalamic sub-regions correlated with physical and psychosocial MFIS. Reduced thalamic RS FC with right insula in motor-, postcentral-, and occipital thalamic sub-regions correlated with psychosocial fatigue.

Conclusion:

Regional thalamic RS FC abnormalities with different cortical regions, including the frontal lobe, sensorimotor network, precuneus, insular cortices, and cerebellum contribute to fatigue in MS. Abnormal RS FC of selected thalamo-cortical connections explains different components of fatigue.

Keywords

Thalamus resting state fMRI MFIS multiple sclerosis

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References

Krupp

Alvarez

LaRocca

. Fatigue in multiple sclerosis. Arch Neurol 1988; 45: 435–437.

Filippi

Rocca

Colombo

. Functional magnetic resonance imaging correlates of fatigue in multiple sclerosis. Neuroimage 2002; 15: 559–567.

Filippi

Rocca

. Toward a definition of structural and functional MRI substrates of fatigue in multiple sclerosis. J Neurol Sci 2007; 263: 1–2.

Bisecco

Caiazzo

d’Ambrosio

. Fatigue in multiple sclerosis: The contribution of occult white matter damage. Mult Scler 2016; 22: 1676–1684.

Mainero

Faroni

Gasperini

. Fatigue and magnetic resonance imaging activity in multiple sclerosis. J Neurol 1999; 246: 454–458.

Riccitelli

Rocca

Forn

. Voxelwise assessment of the regional distribution of damage in the brains of patients with multiple sclerosis and fatigue. Am J Neuroradiol 2011; 32: 874–879.

Rocca

Parisi

Pagani

. Regional but not global brain damage contributes to fatigue in multiple sclerosis. Radiology 2014; 273: 511–520.

Cruz Gomez

Ventura Campos

Belenguer

. Regional brain atrophy and functional connectivity changes related to fatigue in multiple sclerosis. PLoS ONE 2013; 8: e77914.

Gobbi

Rocca

Riccitelli

. Influence of the topography of brain damage on depression and fatigue in patients with multiple sclerosis. Mult Scler 2014; 20: 192–201.

10.

Finke

Schlichting

Papazoglou

. Altered basal ganglia functional connectivity in multiple sclerosis patients with fatigue. Mult Scler 2015; 21: 925–934.

11.

Rocca

Agosta

Colombo

. fMRI changes in relapsing-remitting multiple sclerosis patients complaining of fatigue after IFNbeta-1a injection. Hum Brain Mapp 2007; 28: 373–382.

12.

Rocca

Meani

Riccitelli

. Abnormal adaptation over time of motor network recruitment in multiple sclerosis patients with fatigue. Mult Scler 2016; 22: 1144–1153.

13.

Engstrom

Flensner

Landtblom

. Thalamo-striato-cortical determinants to fatigue in multiple sclerosis. Brain Behav 2013; 3: 715–728.

14.

Minagar

Barnett

Benedict

RHB

. The thalamus and multiple sclerosis: Modern views on pathologic, imaging, and clinical aspects. Neurology 2013; 80: 210–219.

15.

Chaudhuri

Behan

. Fatigue in neurological disorders. Lancet 2004; 363: 978–988.

16.

Wilting

Rolfsnes

Zimmermann

. Structural correlates for fatigue in early relapsing remitting multiple sclerosis. Eur Radiol 2016; 26: 515–523.

17.

Calabrese

Rinaldi

Grossi

. Basal ganglia and frontal/parietal cortical atrophy is associated with fatigue in relapsing-remitting multiple sclerosis. Mult Scler 2010; 16: 1220–1228.

18.

Zhou

Gong

Chen

. Intrinsic functional plasticity of the thalamocortical system in minimally disabled patients with relapsing-remitting multiple sclerosis. Front Hum Neurosci 2016; 10: 2.

19.

DeLuca

Genova

Hillary

. Neural correlates of cognitive fatigue in multiple sclerosis using functional MRI. J Neurol Sci 2008; 270: 28–39.

20.

Genova

Rajagopalan

Deluca

. Examination of cognitive fatigue in multiple sclerosis using functional magnetic resonance imaging and diffusion tensor imaging. PLoS ONE 2013; 8: e78811.

21.

Johansen-Berg

Behrens

Sillery

. Functional-anatomical validation and individual variation of diffusion tractography-based segmentation of the human thalamus. Cereb Cortex 2005; 15: 31–39.

22.

Bisecco

Rocca

Pagani

. Connectivity-based parcellation of the thalamus in multiple sclerosis and its implications for cognitive impairment: A multicenter study. Hum Brain Mapp 2015; 36: 2809–2825.

23.

Amato

Portaccio

Goretti

. The Rao’s Brief Repeatable Battery and Stroop test: Normative values with age, education and gender corrections in an Italian population. Mult Scler 2006; 12: 787–793.

24.

Flachenecker

Kumpfel

Kallmann

. Fatigue in multiple sclerosis: A comparison of different rating scales and correlation to clinical parameters. Mult Scler 2002; 8: 523–526.

25.

Patenaude

Smith

Kennedy

. A Bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage 2011; 56: 907–922.

26.

Biswal

Yetkin

Haughton

. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995; 34: 537–541.

27.

Lowe

Mock

Sorenson

. Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage 1998; 7: 119–132.

28.

Friston

Holmes

Price

. Multisubject fMRI studies and conjunction analyses. Neuroimage 1999; 10: 385–396.

29.

Roelcke

Kappos

Lechner-Scott

. Reduced glucose metabolism in the frontal cortex and basal ganglia of multiple sclerosis patients with fatigue: A 18F-fluorodeoxyglucose positron emission tomography study. Neurology 1997; 48: 1566–1571.

30.

Sbardella

Upadhyay

Tona

. Dentate nucleus connectivity in adult patients with multiple sclerosis: Functional changes at rest and correlation with clinical features. Mult Scler 2017; 23: 546–555.

31.

Stoodley

Valera

Schmahmann

. Functional topography of the cerebellum for motor and cognitive tasks: An fMRI study. Neuroimage 2012; 59: 1560–1570.

32.

Yang

Raine

. Prefrontal structural and functional brain imaging findings in antisocial, violent, and psychopathic individuals: A meta-analysis. Psychiatry Res 2009; 174: 81–88.

33.

Mills

Young

Pallant

. Rasch analysis of the Modified Fatigue Impact Scale (MFIS) in multiple sclerosis. J Neurol Neurosurg Psychiatry 2010; 81: 1049–1051.

34.

Yang

. Neural systems underlying emotional and non-emotional interference processing: An ALE meta-analysis of functional neuroimaging studies. Front Behav Neurosci 2016; 10: 220.

35.

Rottoli

La Gioia

Frigeni

. Pathophysiology, assessment and management of multiple sclerosis fatigue: An update. Expert Rev Neurother 2017; 17: 373–379.

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