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Structural correlates for fatigue in early relapsing remitting multiple sclerosis

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Abstract

Objectives

Fatigue is a common symptom in multiple sclerosis (MS) patients, even early in the disease, but the pathophysiology remains unclear. We aimed to determine morphologic and microstructural correlates and neuropsychological parameters of cognitive fatigue in early relapsing-remitting MS patients.

Methods

Seventy-nine early relapsing-remitting MS patients (38 with fatigue and 41 without), none of whom suffered from depression, underwent neuropsychological testing. Magnetic resonance imaging was performed using anatomical and diffusion tensor imaging sequences on all patients and 40 controls. Voxel-based morphologic analysis and tract-based spatial statistics were performed.

Results

Only patients with cognitive fatigue, but not those without, exhibited alterations in the thalamic region, showing reduced thalamic fractional anisotropy and increased mean diffusivity values. No differences in lesion volume and lesion distribution were observed between patient groups. In cognitive tests, no significant differences were found between the two groups in the number of patients with pathologic scores; however, subjective cognitive impairment differed.

Conclusion

Morphological alterations and distinct microstructural changes (mainly in the thalamus) but not typical MS lesions were found to be related to cognitive fatigue in early MS. We suggest that compensatory processes adapting to these changes could initially facilitate normal cognitive performance, but also result in a feeling of fatigue.

Key points

Morphological alterations and microstructural changes are related to fatigue in multiple sclerosis

Thalamic alterations in particular were related to fatigue in early MS

Fatigued patients exhibited subjective but not measurable cognitive impairment

Compensatory processes help preserve or maintain cognitive performance but also contribute to fatigue

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References

  1. Engel C, Greim B, Zettl UK (2007) Diagnostics of cognitive dysfunctions in multiple sclerosis. J Neurol 254:II30–II34

    PubMed  Google Scholar 

  2. Freal JE, Kraft GH, Coryell JK (1984) Symptomatic fatigue in multiple sclerosis. Arch Phys Med Rehabil 65:135–138

    PubMed  CAS  Google Scholar 

  3. Bobholz JA, Rao SM (2003) Cognitive dysfunction in multiple sclerosis: a review of recent developments. Curr Opin Neurol 16:283–288

    Article  PubMed  Google Scholar 

  4. Morrow SA, Weinstock-Guttman B, Munschauer FE, Hojnacki D, Benedict RH (2009) Subjective fatigue is not associated with cognitive impairment in multiple sclerosis: cross-sectional and longitudinal analysis. Mult Scler 15:998–1005

    Article  PubMed  CAS  Google Scholar 

  5. Jougleux-Vie C, Duhin E, Deken V, Outteryck O, Vermersch P, Zephir H (2014) Does fatigue complaint reflect memory impairment in multiple sclerosis? Mult Scler Int 2014:692468

    PubMed  PubMed Central  Google Scholar 

  6. Neumann M, Sterr A, Claros-Salinas D, Gutler R, Ulrich R, Dettmers C (2014) Modulation of alertness by sustained cognitive demand in MS as surrogate measure of fatigue and fatigability. J Neurol Sci 340:178–182

    Article  PubMed  Google Scholar 

  7. Niepel G, Bibani RH, Vilisaar J et al (2013) Association of a deficit of arousal with fatigue in multiple sclerosis: effect of modafinil. Neuropharmacology 64:380–388

    Article  PubMed  CAS  Google Scholar 

  8. Weinges-Evers N, Brandt AU, Bock M et al (2010) Correlation of self-assessed fatigue and alertness in multiple sclerosis. Mult Scler 16:1134–1140

    Article  PubMed  Google Scholar 

  9. MSCfCP (1998) Fatigue and multiple sclerosis: evidence-based management strategies for fatigue in multiple sclerosis. Multiple Sclerosis Council for Clinical Practice Guidelines

  10. Bakshi R, Shaikh ZA, Miletich RS et al (2000) Fatigue in multiple sclerosis and its relationship to depression and neurologic disability. Mult Scler 6:181–185

    Article  PubMed  CAS  Google Scholar 

  11. Rocca MA, Mesaros S, Pagani E, Sormani MP, Comi G, Filippi M (2010) Thalamic damage and long-term progression of disability in multiple sclerosis. Radiology 257:463–469

    Article  PubMed  Google Scholar 

  12. Calabrese M, Rinaldi F, Grossi P et al (2010) Basal ganglia and frontal/parietal cortical atrophy is associated with fatigue in relapsing-remitting multiple sclerosis. Mult Scler 16:1220–1228

    Article  PubMed  Google Scholar 

  13. Genova HM, Rajagopalan V, Deluca J et al (2013) Examination of cognitive fatigue in multiple sclerosis using functional magnetic resonance imaging and diffusion tensor imaging. PLoS One 8, e78811

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  14. Chaudhuri A, Behan PO (2000) Fatigue and basal ganglia. J Neurol Sci 179:34–42

    Article  PubMed  CAS  Google Scholar 

  15. Sepulcre J, Masdeu JC, Goni J et al (2009) Fatigue in multiple sclerosis is associated with the disruption of frontal and parietal pathways. Mult Scler 15:337–344

    Article  PubMed  CAS  Google Scholar 

  16. Pellicano C, Gallo A, Li X et al (2010) Relationship of cortical atrophy to fatigue in patients with multiple sclerosis. Arch Neurol 67:447–453

    Article  PubMed  Google Scholar 

  17. DeLuca J, Genova HM, Hillary FG, Wylie G (2008) Neural correlates of cognitive fatigue in multiple sclerosis using functional MRI. J Neurol Sci 270:28–39

    Article  PubMed  Google Scholar 

  18. Riccitelli G, Rocca MA, Forn C, Colombo B, Comi G, Filippi M (2011) Voxelwise assessment of the regional distribution of damage in the brains of patients with multiple sclerosis and fatigue. AJNR Am J Neuroradiol 32:874–879

    Article  PubMed  CAS  Google Scholar 

  19. Gobbi C, Rocca MA, Riccitelli G et al (2014) Influence of the topography of brain damage on depression and fatigue in patients with multiple sclerosis. Mult Scler 20:192–201

    Article  PubMed  CAS  Google Scholar 

  20. Bester M, Lazar M, Petracca M et al (2013) Tract-specific white matter correlates of fatigue and cognitive impairment in benign multiple sclerosis. J Neurol Sci 330:61–66

    Article  PubMed  PubMed Central  Google Scholar 

  21. Polman CH, Reingold SC, Banwell B et al (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69:292–302

    Article  PubMed  PubMed Central  Google Scholar 

  22. Penner IK, Raselli C, Stöcklin M, Opwis K, Kappos L, Calabrese P (2009) The Fatigue Scale for Motor and Cognitive Functions (FSMC): validation of a new instrument to assess multiple sclerosis-related fatigue. Mult Scler 15:1509–1517

    Article  PubMed  CAS  Google Scholar 

  23. Schmidt P, Gaser C, Arsic M et al (2012) An automated tool for detection of FLAIR-hyperintense white-matter lesions in multiple sclerosis. Neuroimage 59:3774–3783

    Article  PubMed  Google Scholar 

  24. Rudick RA, Fisher E, Lee JC, Simon J, Jacobs L (1999) Use of the brain parenchymal fraction to measure whole brain atrophy in relapsing-remitting MS. Multiple Sclerosis Collaborative Research Group. Neurology 53:1698–1704

    Article  PubMed  CAS  Google Scholar 

  25. Chard DT, Parker GJ, Griffin CM, Thompson AJ, Miller DH (2002) The reproducibility and sensitivity of brain tissue volume measurements derived from an SPM-based segmentation methodology. J Magn Reson Imaging 15:259–267

    Article  PubMed  Google Scholar 

  26. Smith SM, Jenkinson M, Johansen-Berg H et al (2006) Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31:1487–1505

    Article  PubMed  Google Scholar 

  27. Smith SM, Nichols TE (2009) Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 44:83–98

    Article  PubMed  Google Scholar 

  28. Takao H, Hayashi N, Ohtomo K (2014) Sex dimorphism in the white matter: fractional anisotropy and brain size. J Magn Reson Imaging 39:917–923

    Article  PubMed  Google Scholar 

  29. Harrison DM, Oh J, Roy S et al (2015) Thalamic lesions in multiple sclerosis by 7T MRI: clinical implications and relationship to cortical pathology. Mult Scler. doi:10.1177/1352458514558134

    Google Scholar 

  30. Engstrom M, Flensner G, Landtblom AM, Ek AC, Karlsson T (2013) Thalamo-striato-cortical determinants to fatigue in multiple sclerosis. Brain Behav 3:715–728

    Article  PubMed  PubMed Central  Google Scholar 

  31. Lansley J, Mataix-Cols D, Grau M, Radua J, Sastre-Garriga J (2013) Localized grey matter atrophy in multiple sclerosis: a meta-analysis of voxel-based morphometry studies and associations with functional disability. Neurosci Biobehav Rev 37:819–830

    Article  PubMed  CAS  Google Scholar 

  32. Mesaros S, Rocca MA, Absinta M et al (2008) Evidence of thalamic gray matter loss in pediatric multiple sclerosis. Neurology 70:1107–1112

    Article  PubMed  CAS  Google Scholar 

  33. Wylezinska M, Cifelli A, Jezzard P, Palace J, Alecci M, Matthews PM (2003) Thalamic neurodegeneration in relapsing-remitting multiple sclerosis. Neurology 60:1949–1954

    Article  PubMed  CAS  Google Scholar 

  34. Tedeschi G, Dinacci D, Lavorgna L et al (2007) Correlation between fatigue and brain atrophy and lesion load in multiple sclerosis patients independent of disability. J Neurol Sci 263:15–19

    Article  PubMed  Google Scholar 

  35. Marrie RA, Fisher E, Miller DM, Lee JC, Rudick RA (2005) Association of fatigue and brain atrophy in multiple sclerosis. J Neurol Sci 228:161–166

    Article  PubMed  Google Scholar 

  36. Rocca MA, Parisi L, Pagani E et al (2014) Regional but not global brain damage contributes to fatigue in multiple sclerosis. Radiology 273:511–520

    Article  PubMed  Google Scholar 

  37. Calabrese P, Penner IK (2007) Cognitive dysfunctions in multiple sclerosis–a “multiple disconnection syndrome”? J Neurol 254:II18–II21

    PubMed  Google Scholar 

  38. Penner IK, Rausch M, Kappos L, Opwis K, Radu EW (2003) Analysis of impairment related functional architecture in MS patients during performance of different attention tasks. J Neurol 250:461–472

    Article  PubMed  Google Scholar 

  39. Hoffmann S, Tittgemeyer M, von Cramon DY (2007) Cognitive impairment in multiple sclerosis. Curr Opin Neurol 20:275–280

    Article  PubMed  Google Scholar 

  40. Nocentini U, Pasqualetti P, Bonavita S et al (2006) Cognitive dysfunction in patients with relapsing-remitting multiple sclerosis. Mult Scler 12:77–87

    Article  PubMed  CAS  Google Scholar 

  41. Andreasen AK, Spliid PE, Andersen H, Jakobsen J (2010) Fatigue and processing speed are related in multiple sclerosis. Eur J Neurol 17:212–218

    Article  PubMed  CAS  Google Scholar 

  42. Van Hecke W, Nagels G, Leemans A, Vandervliet E, Sijbers J, Parizel PM (2010) Correlation of cognitive dysfunction and diffusion tensor MRI measures in patients with mild and moderate multiple sclerosis. J Magn Reson Imaging 31:1492–1498

    Article  PubMed  Google Scholar 

  43. Akbar N, Honarmand K, Feinstein A (2011) Self-assessment of cognition in multiple sclerosis: the role of personality and anxiety. Cogn Behav Neurol 24:115–121

    Article  PubMed  Google Scholar 

  44. Bove R, Musallam A, Healy BC et al (2013) No sex-specific difference in disease trajectory in multiple sclerosis patients before and after age 50. BMC Neurol 13:73

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The scientific guarantor of this publication is Frauke Zipp. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. This study has received funding by the Ministry of Science and Education/German Competence Network for Multiple Sclerosis (BMBF/KKNMS, B7.3 to FZ). No complex statistical methods were necessary for this paper. Institutional review board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. No study subjects or cohorts have been previously reported. Methodology: retrospective, cross sectional study, performed at one institution.

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Correspondence to Adriane Gröger.

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Frauke Zipp and Adriane Gröger contributed equally to this work.

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Wilting, J., Rolfsnes, H.O., Zimmermann, H. et al. Structural correlates for fatigue in early relapsing remitting multiple sclerosis. Eur Radiol 26, 515–523 (2016). https://doi.org/10.1007/s00330-015-3857-2

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  • DOI: https://doi.org/10.1007/s00330-015-3857-2

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