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Nucleus basalis of Meynert damage and cognition in patients with multiple sclerosis

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Abstract

Background

The nucleus basalis of Meynert (NBM), representing the major source of cerebral cholinergic innervations, is vulnerable to neurodegeneration in Alzheimer’s and Parkinson’s disease.

Objective

To determine associations between NBM properties and cognitive outcomes in patients with multiple sclerosis (PwMS).

Methods

84 PwMS and 19 controls underwent 3T MRI, the Paced Auditory Serial Addition Test (PASAT) and subtests of the Brief International Cognitive Assessment for MS (BICAMS). NBM volume, fractional anisotropy, mean diffusivity (MD), axial diffusivity and radial diffusivity (D⊥) were calculated. Analyses assessed relationships between cognition and NBM measures. Linear regressions evaluated the prognostic value of baseline measures in predicting cognitive change over 3 years of follow-up (n = 67).

Results

Cognitive tests correlated with NBM diffusivity in PwMS (range r = – 0.29 to r = – 0.40, p < 0.05). After accounting for NBM volume, NBM MD and D⊥ explained additional variance (adjusted R2 range 0.08–0.20, p < 0.05). Correlations between NBM imaging metrics and cognitive tests remained significant when including imaging parameters of other cognitive key brain regions in the models. After controlling for age, education, and baseline cognitive test score, NBM measures predicted change in cognition over follow-up in 5 of 10 and 2 of 10 assessments in the relapsing–remitting sample (n = 43) (adjusted R2 range from 0.23 to 0.38, p < 0.05) and secondary progressive sample (adjusted R2 of 0.280 and 0.183), respectively.

Conclusions

NBM damage is linked to cognitive impairment in PwMS.

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Abbreviations

ACh:

Acetylcholine

AD:

Alzheimer’s disease

ANCOVA:

Analysis of covariance

BICAMS:

Brief International Cognitive Assessment for MS

BVMT-R:

Brief Visuospatial Memory Test Revised

CVLT-2:

California Verbal Learning Test second edition

DTI:

Diffusion tensor imaging

\({\text{D}}_{\parallel }\) :

Axial diffusivity

\({\text{D}}_{ \bot }\) :

Radial diffusivity

FA:

Fractional anisotropy

FIRST:

FMRIB’s Integrated Registration and Segmentation Tool

FLAIR:

Fluid-attenuated inversion recovery

GM:

Gray matter

IQR:

Interquartile range

LV:

Lesion volume

MD:

Mean diffusivity

MS:

Multiple sclerosis

NAWB:

Normal-appearing whole brain

NBM:

Nucleus basalis of Meynert

NP:

Neuropsychological

PASAT:

Paced Auditory Serial Addition Test

PD:

Parkinson’s disease

PwMS:

Patients with MS

RRMS:

Relapsing–remitting multiple sclerosis

SDMT:

Symbol Digit Modalities Test

SIENAX:

Structural Image Evaluation, using Normalisation, of Atrophy—X-sectional

SPMS:

Secondary progressive multiple sclerosis

WM:

White matter

WB:

Whole brain

References

  1. Nemy M, Cedres N, Grothe MJ, Muehlboeck JS, Lindberg O, Nedelska Z et al (2020) Cholinergic white matter pathways make a stronger contribution to attention and memory in normal aging than cerebrovascular health and nucleus basalis of Meynert. Neuroimage 211:116607

    Article  Google Scholar 

  2. Koulousakis P, Andrade P, Visser-Vandewalle V, Sesia T (2019) The nucleus basalis of meynert and its role in deep brain stimulation for cognitive disorders: a historical perspective. J Alzheimer’s Dis 69(4):905–919

    Article  Google Scholar 

  3. Mesulam M (2013) Cholinergic circuitry of the human nucleus basalis and its fate in Alzheimer`s disease. J Comp Neurol 521(18):4124–4144

    Article  CAS  Google Scholar 

  4. Bohnen NI, Albin RL (2011) The cholinergic system in Parkinson’s disease. Behav Brain Res 221(2):564–573

    Article  CAS  Google Scholar 

  5. Mesulam M, Mufson EJ, Levey AI, Wainer BH (1983) Cholinergic innervation of cortex by the basal forebrain: Cytochemistry and cortical connections of the septal area, diagonal band nuclei, nucleus basalis (Substantia innominata), and hypothalamus in the rhesus monkey. J Comp Neurol 214:170–197

    Article  CAS  Google Scholar 

  6. Schulz J, Pagano G, Fernández Bonfante JA, Wilson H, Politis M (2018) Nucleus Basalis of Meynert degeneration precedes and predicts cognitive impairment in Parkinson’s disease. Brain 141(5):1501–1516

    Article  Google Scholar 

  7. Shu SY, Jiang G, Zheng Z, Ma L, Wang B, Zeng Q et al (2019) A new neural pathway from the ventral striatum to the nucleus Basalis of Meynert with functional implication to learning and memory. Mol Neurobiol 56(10):7222–7233

    Article  CAS  Google Scholar 

  8. Jethwa KD, Dhillon P, Meng D, Auer DP (2019) Are linear measurements of the nucleus basalis of Meynert suitable as a diagnostic biomarker in mild cognitive impairment and Alzheimer disease? Am J Neuroradiol 40(12):2039–2044

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Tata AM, Velluto L, D'Angelo C, Reale M (2014) Cholinergic system dysfunction and neurodegenerative diseases: cause or effect? CNS Neurol Disord Drug Targets 13(7):1294–1303

    Article  CAS  Google Scholar 

  10. Gang M, Baba T, Hosokai Y, Nishio Y, Kikuchi A, Hirayama K et al (2020) Clinical and cerebral metabolic changes in Parkinson’s disease with basal forebrain atrophy. Mov Disord 35(5):825–832

    Article  Google Scholar 

  11. Hepp DH, Foncke EMJ, Berendse HW, Wassenaar TM, Olde Dubbelink KTE, Groenewegen HJ et al (2017) Damaged fiber tracts of the nucleus basalis of Meynert in Parkinson’s disease patients with visual hallucinations. Sci Rep 7(1):1–10

    Article  CAS  Google Scholar 

  12. Bohnen NI, Mueller MLTM, Kotagal V, Koeppe RA, Kilbourn MR, Gilman S et al (2012) Heterogeneity of cholinergic denervation in Parkinson’s disease without dementia. J Cereb Blood Flow Metab 32:1609–1617

    Article  CAS  Google Scholar 

  13. Brueggen K, Dyrba M, Barkhof F, Hausner L, Filippi M, Nestor PJ et al (2015) Basal forebrain and hippocampus as predictors of conversion to Alzheimer’s disease in patients with mild cognitive impairment-a multicenter DTI and volumetry study. J Alzheimer’s Dis 48(1):197–204

    Article  Google Scholar 

  14. Teipel SJ, Meindl T, Grinberg L, Grothe M, Cantero JL, Reiser MF et al (2011) The cholinergic system in mild cognitive impairment and Alzheimer´s disease: an in vivo MRI and DTI study. Hum Brain Mapp 32(9):1349–1362

    Article  Google Scholar 

  15. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M et al (2011) Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria. Ann Neurol 69(2):292–302

    Article  Google Scholar 

  16. Zivadinov R, Heininen-Brown M, Schirda CV, Poloni GU, Bergsland N, Magnano CR et al (2012) Abnormal subcortical deep-gray matter susceptibility-weighted imaging filtered phase measurements in patients with multiple sclerosis. A case-control study. Neuroimage 59(1):331–339

    Article  Google Scholar 

  17. Dwyer MG, Bergsland N, Zivadinov R (2014) Improved longitudinal gray and white matter atrophy assessment via application of a 4-dimensional hidden Markov random field model. Neuroimage 90:207–217

    Article  Google Scholar 

  18. Patenaude B, Smith SM, Kennedy DN, Jenkinson M (2011) A Bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage 56:907–922

    Article  Google Scholar 

  19. Benedict RHB, Hulst HE, Bergsland N, Schoonheim MM, Dwyer MG, Weinstock-Guttman B et al (2013) Clinical significance of atrophy and white matter mean diffusivity within the thalamus of multiple sclerosis patients. Mult Scler J 19(11):1478–1484

    Article  Google Scholar 

  20. Benedict RHB, Amato MP, Boringa J, Brochet B, Foley F, Fredrikson S et al (2012) Brief International Cognitive Assessment for MS (BICAMS): international standards for validation. BMC Neurol 12(55):1–8

    Google Scholar 

  21. Benedict RHB, DeLuca J, Phillips G, LaRocca N, Hudson LD, Rudick R et al (2017) Validity of the Symbol Digit Modalities Test as a cognition performance outcome measure for multiple sclerosis. Mult Scler 23(5):721–733

    Article  Google Scholar 

  22. Brochet B, Ruet A (2019) Cognitive impairment in multiple sclerosis with regards to disease duration and clinical phenotypes. Front Neurol 10:261

    Article  Google Scholar 

  23. Lope-Piedrafita S (2018) Diffusion tensor imaging (DTI). In: Garcia-Martin ML, Lopez-Larrubia P (eds) Preclinical MRI: methods and protocols, methods in molecular biology, pp 103–116

  24. Song SK, Sun SW, Ramsbottom MJ, Chang C, Russell J, Cross AH (2002) Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. Neuroimage 17(3):1429–1436

    Article  Google Scholar 

  25. Eijlers AJC, Dekker I, Steenwijk MD, Meijer KA, Hulst HE, Pouwels PJW et al (2019) Cortical atrophy accelerates as cognitive decline worsens in multiple sclerosis. Neurology 93(14):E1348–E1359

    Article  Google Scholar 

  26. Charalambous T, Tur C, Prados F, Kanber B, Chard DT, Ourselin S et al (2018) Structural network disruption markers explain disability in multiple sclerosis. J Neurol Neurosurg Psychiatry 90(2):219–226

    Article  Google Scholar 

  27. Nizri E, Hamra-Amitay Y, Sicsic C, Lavon I, Benner T (2006) Anti-inflammatory properties of cholinergic up-regulation: A new role for acetylcholinesterase inhibitors. Neuropharmacology 50:540–547

    Article  CAS  Google Scholar 

  28. Pavlov VA, Parrish WR, Rosas-Ballina M, Ochani M, Puerta M, Ochani K et al (2009) Brain acetylcholinesterase activity controls systemic cytokine levels through the cholinergic anti-inflammatory pathway. Brain Behav Immun 23(1):41–45

    Article  CAS  Google Scholar 

  29. Reale M, Costantini E, Di Nicola M, D’Angelo C, Franchi S, D’Aurora M et al (2018) Butyrylcholinesterase and acetylcholinesterase polymorphisms in multiple sclerosis patients: implication in peripheral inflammation. Sci Rep 8:1319

    Article  Google Scholar 

  30. Di Bari M, Di Pinto G, Reale M, Mengod G, Tata AM (2017) Cholinergic system and neuroinflammation: implication in multiple sclerosis. Cent Nerv Syst Agents Med Chem 17:1–7

    Article  Google Scholar 

  31. Gatta V, Mengod G, Reale M, Tata AM (2020) Possible correlation between cholinergic system alterations and neuro/inflammation in multiple sclerosis. Biomedicines 8:153

    Article  CAS  Google Scholar 

  32. Polachini CRN, Spanevello RM, Schetinger MRC, Morsch VM (2018) Cholinergic and purinergic systems: a key to multiple sclerosis? J Neurol Sci 392:8–21

    Article  CAS  Google Scholar 

  33. Christodoulou C, Melville P, Scherl WF, Macallister WS, Elkins LE, Krupp LB (2006) Effects of donepezil on memory and cognition in multiple sclerosis. J Neurol Sci 245:127–136

    Article  CAS  Google Scholar 

  34. Krupp LB, Christodoulou C, Melville P, Scherl WF, Pai LY, Muenz LR et al (2011) Multicenter randomized clinical trial of donepezil for memory impairment in multiple sclerosis. Neurology 76(17):1500–1507

    Article  CAS  Google Scholar 

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Funding

The research reported in this publication was funded by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UL1TR001412. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

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Authors and Affiliations

  1. Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 100 High St., Buffalo, NY, 14203, USA

    Franziska E. Hildesheim, Robert Zivadinov, Michael G. Dwyer, Tom Fuchs, Dejan Jakimovski & Niels Bergsland

  2. Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, Jacobs Comprehensive MS Treatment and Research Center, University at Buffalo, Buffalo, NY, USA

    Ralph H. B. Benedict & Bianca Weinstock-Guttman

  3. Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA

    Robert Zivadinov & Michael G. Dwyer

  4. IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy

    Niels Bergsland

Authors
  1. Franziska E. Hildesheim
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  2. Ralph H. B. Benedict
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  3. Robert Zivadinov
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  4. Michael G. Dwyer
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Corresponding author

Correspondence to Niels Bergsland.

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Conflicts of interest

Franziska Hildesheim, Tom Fuchs, Dejan Jakimovski, and Niels Bergsland have nothing to disclose. Ralph H. B. Benedict has received research support from Accorda, Novartis, Genzyme, Biogen Idec, and Mallinkrodt, and is on the speakers’ bureau for EMD Serono, and consults for Biogen Idec, Genentech, Roche, Sanofi/Genzyme, Takeda, NeuroCog Trials, and Novartis. Dr. Benedict also receives royalties for Psychological Assessment Resources. Robert Zivadinov received personal compensation from EMD Serono, Sanofi, Bristol Myers Squibb, Keystone Heart and Novartis for speaking and consultant fees. He received financial support for research activities from Novartis, Protembis, Bristol Myers Squibb, Keystone Heart, Mapi Pharma, V-WAVE Medical and Boston Scientific. Michael G. Dwyer has received consultant fees from Claret Medical and EMD Serono and research grant support from Novartis. Bianca Weinstock-Guttman received honoraria as a speaker and/or as a consultant for Biogen Idec, EMD Serono, Genentech, Novartis, Mallinckrodt, Celgene, Abbvie. Dr Weinstock-Guttman received research funds from Biogen Idec, EMD Serono, Genentech, and Novartis.

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Hildesheim, F.E., Benedict, R.H.B., Zivadinov, R. et al. Nucleus basalis of Meynert damage and cognition in patients with multiple sclerosis. J Neurol 268, 4796–4808 (2021). https://doi.org/10.1007/s00415-021-10594-7

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  • DOI: https://doi.org/10.1007/s00415-021-10594-7

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