Skip to main content

Advertisement

SpringerLink
Log in

Visual deficits and cognitive assessment of multiple sclerosis: confounder, correlate, or both?

  • Original Communication
  • Published:
Journal of Neurology Aims and scope Submit manuscript

Abstract

Background

The relationship between visual impairment and cognitive performance in multiple sclerosis (MS) remains poorly understood.

Objective

To determine associations between visual acuity and optical coherence tomography (OCT) measures with cognitive performance of MS patients and healthy controls (HCs).

Methods

141 MS patients (with and without MS optic neuritis; MSON) and 50 HCs underwent neuropsychological, visual, and OCT testing. California Verbal Learning Test (CVLT-II), Brief Visuospatial Memory Test (BVMT-R), and Symbol Digit Modalities Test (SDMT) were used. Patients with test performance below − 1.5 standard deviations of the mean HCs scores were labeled as cognitive impairment. Visual ability was assessed with 100%, 2.5%, and 1.25% low-contrast letter acuity (LCLA) charts. OCT-derived peripapillary retinal nerve fiber layer (pRNFL) thickness, macular volume (MV), macular ganglion cell inner plexiform (mGCIP) thickness (as a sum of GC and IP layers), and macular inner nuclear layer (mINL) were computed.

Results

100% and 2.5% LCLA associated with SDMT in MS and HCs (p < 0.001; and p < 0.012, respectively). In MSON patients, visually demanding tests were explained by pRNFL and macular volume for SDMT (β = 0.172, p = 0.039 and β = 0.27, p = 0.001) and MV for BVMT-R (β = 0.21, p = 0.012). In non-MSON, only mINL was predictor of CVLT-II. pRNFL and MV predicted cognitive impairment with an accuracy of 72.2% (Negelkerke R2 = 0.234). These findings were driven by associations within the progressive MS subgroup. HC’s SDMT performance was explained by mGCIP (β = 0.316, p = 0.001).

Conclusions

Both LCLA and OCT-based measures (pRNFL and macular volume) were associated with MS cognitive performance. OCT-based measures were also significant predictors of cognitive status in MS patients. mGCIP associated with cognitive performance in HCs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Benedict RH, Pol J, Yasin F, Hojnacki D, Kolb C, Eckert S, Tacca B, Drake A, Wojcik C, Morrow SA, Jakimovski D, Fuchs TA, Dwyer MG, Zivadinov R, Weinstock-Guttman B (2020) Recovery of cognitive function after relapse in multiple sclerosis. Mult Scler. https://doi.org/10.1177/1352458519898108

    Article  PubMed  PubMed Central  Google Scholar 

  2. Benedict RH, Zivadinov R (2011) Risk factors for and management of cognitive dysfunction in multiple sclerosis. Nat Rev Neurol 7(6):332–342. https://doi.org/10.1038/nrneurol.2011.61

    Article  PubMed  Google Scholar 

  3. Balcer LJ (2006) Clinical practice. Optic neuritis. N Engl J Med 354(12):1273–1280. https://doi.org/10.1056/NEJMcp053247

    Article  CAS  PubMed  Google Scholar 

  4. Balcer LJ, Raynowska J, Nolan R, Galetta SL, Kapoor R, Benedict R, Phillips G, LaRocca N, Hudson L, Rudick R, Multiple Sclerosis Outcome Assessments C (2017) Validity of low-contrast letter acuity as a visual performance outcome measure for multiple sclerosis. Mult Scler 23(5):734–747. https://doi.org/10.1177/1352458517690822

    Article  PubMed  PubMed Central  Google Scholar 

  5. Tavazzi E, Jakimovski D, Kuhle J, Hagemeier J, Ozel O, Ramanathan M, Barro C, Bergsland N, Tomic D, Kropshofer H, Leppert D, Michalak Z, Lincoff N, Dwyer MG, Benedict RHB, Weinstock-Guttman B, Zivadinov R (2020) Serum neurofilament light chain and optical coherence tomography measures in MS: a longitudinal study. Neurol Neuroimmunol Neuroinflamm. https://doi.org/10.1212/NXI.0000000000000737

    Article  PubMed  PubMed Central  Google Scholar 

  6. Alonso R, Gonzalez-Moron D, Garcea O (2018) Optical coherence tomography as a biomarker of neurodegeneration in multiple sclerosis: a review. Mult Scler Relat Disord 22:77–82. https://doi.org/10.1016/j.msard.2018.03.007

    Article  PubMed  Google Scholar 

  7. Gupta S, Zivadinov R, Ramanathan M, Weinstock-Guttman B (2016) Optical coherence tomography and neurodegeneration: are eyes the windows to the brain? Expert Rev Neurother 16(7):765–775. https://doi.org/10.1080/14737175.2016.1180978

    Article  CAS  PubMed  Google Scholar 

  8. Gordon-Lipkin E, Chodkowski B, Reich DS, Smith SA, Pulicken M, Balcer LJ, Frohman EM, Cutter G, Calabresi PA (2007) Retinal nerve fiber layer is associated with brain atrophy in multiple sclerosis. Neurology 69(16):1603–1609. https://doi.org/10.1212/01.wnl.0000295995.46586.ae

    Article  CAS  PubMed  Google Scholar 

  9. Saidha S, Al-Louzi O, Ratchford JN, Bhargava P, Oh J, Newsome SD, Prince JL, Pham D, Roy S, van Zijl P, Balcer LJ, Frohman EM, Reich DS, Crainiceanu C, Calabresi PA (2015) Optical coherence tomography reflects brain atrophy in multiple sclerosis: a four-year study. Ann Neurol 78(5):801–813. https://doi.org/10.1002/ana.24487

    Article  PubMed  PubMed Central  Google Scholar 

  10. Talman LS, Bisker ER, Sackel DJ, Long DA Jr, Galetta KM, Ratchford JN, Lile DJ, Farrell SK, Loguidice MJ, Remington G, Conger A, Frohman TC, Jacobs DA, Markowitz CE, Cutter GR, Ying GS, Dai Y, Maguire MG, Galetta SL, Frohman EM, Calabresi PA, Balcer LJ (2010) Longitudinal study of vision and retinal nerve fiber layer thickness in multiple sclerosis. Ann Neurol 67(6):749–760. https://doi.org/10.1002/ana.22005

    Article  PubMed  PubMed Central  Google Scholar 

  11. Fisher JB, Jacobs DA, Markowitz CE, Galetta SL, Volpe NJ, Nano-Schiavi ML, Baier ML, Frohman EM, Winslow H, Frohman TC, Calabresi PA, Maguire MG, Cutter GR, Balcer LJ (2006) Relation of visual function to retinal nerve fiber layer thickness in multiple sclerosis. Ophthalmology 113(2):324–332. https://doi.org/10.1016/j.ophtha.2005.10.040

    Article  PubMed  Google Scholar 

  12. Jakimovski D, Ramanathan M, Weinstock-Guttman B, Bergsland N, Ramasamay DP, Carl E, Dwyer MG, Zivadinov R (2019) Higher EBV response is associated with more severe gray matter and lesion pathology in relapsing multiple sclerosis patients: a case-controlled magnetization transfer ratio study. Mult Scler. https://doi.org/10.1177/1352458519828667

    Article  PubMed  PubMed Central  Google Scholar 

  13. Jakimovski D, Benedict RH, Marr K, Gandhi S, Bergsland N, Weinstock-Guttman B, Zivadinov R (2019) Lower total cerebral arterial flow contributes to cognitive performance in multiple sclerosis patients. Mult Scler: https://doi.org/10.1177/1352458518819608

    Article  Google Scholar 

  14. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, Fujihara K, Havrdova E, Hutchinson M, Kappos L, Lublin FD, Montalban X, O’Connor P, Sandberg-Wollheim M, Thompson AJ, Waubant E, Weinshenker B, Wolinsky JS (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69(2):292–302. https://doi.org/10.1002/ana.22366

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33(11):1444–1452. https://doi.org/10.1212/wnl.33.11.1444

    Article  CAS  PubMed  Google Scholar 

  16. Roxburgh RH, Seaman SR, Masterman T, Hensiek AE, Sawcer SJ, Vukusic S, Achiti I, Confavreux C, Coustans M, le Page E, Edan G, McDonnell GV, Hawkins S, Trojano M, Liguori M, Cocco E, Marrosu MG, Tesser F, Leone MA, Weber A, Zipp F, Miterski B, Epplen JT, Oturai A, Sorensen PS, Celius EG, Lara NT, Montalban X, Villoslada P, Silva AM, Marta M, Leite I, Dubois B, Rubio J, Butzkueven H, Kilpatrick T, Mycko MP, Selmaj KW, Rio ME, Sa M, Salemi G, Savettieri G, Hillert J, Compston DA (2005) Multiple Sclerosis Severity Score: using disability and disease duration to rate disease severity. Neurology 64(7):1144–1151. https://doi.org/10.1212/01.WNL.0000156155.19270.F8

    Article  CAS  PubMed  Google Scholar 

  17. Tewarie P, Balk L, Costello F, Green A, Martin R, Schippling S, Petzold A (2012) The OSCAR-IB consensus criteria for retinal OCT quality assessment. PLoS ONE 7(4):e34823. https://doi.org/10.1371/journal.pone.0034823

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Nguyen J, Rothman A, Fitzgerald K, Whetstone A, Syc-Mazurek S, Aquino J, Balcer LJ, Frohman EM, Frohman TC, Crainiceanu C, Beier M, Newsome SD, Calabresi PA, Saidha S (2018) Visual pathway measures are associated with neuropsychological function in multiple sclerosis. Curr Eye Res 43(7):941–948. https://doi.org/10.1080/02713683.2018.1459730

    Article  PubMed  PubMed Central  Google Scholar 

  19. Wieder L, Gade G, Pech LM, Zimmermann H, Wernecke KD, Dorr JM, Bellmann-Strobl J, Paul F, Brandt AU (2013) Low contrast visual acuity testing is associated with cognitive performance in multiple sclerosis: a cross-sectional pilot study. BMC Neurol 13:167. https://doi.org/10.1186/1471-2377-13-167

    Article  PubMed  PubMed Central  Google Scholar 

  20. Bruce JM, Bruce AS, Arnett PA (2007) Mild visual acuity disturbances are associated with performance on tests of complex visual attention in MS. J Int Neuropsychol Soc 13(3):544–548. https://doi.org/10.1017/S1355617707070658

    Article  PubMed  Google Scholar 

  21. Anhoque CF, Biccas-Neto L, Domingues SC, Teixeira AL, Domingues RB (2013) Cognitive impairment and optic nerve axonal loss in patients with clinically isolated syndrome. Clin Neurol Neurosurg 115(7):1032–1035. https://doi.org/10.1016/j.clineuro.2012.10.025

    Article  CAS  PubMed  Google Scholar 

  22. Birkeldh U, Manouchehrinia A, Hietala MA, Hillert J, Olsson T, Piehl F, Kockum I, Brundin L, Zahavi O, Wahlberg-Ramsay M, Brautaset R, Nilsson M (2019) Retinal nerve fiber layer thickness associates with cognitive impairment and physical disability in multiple sclerosis. Mult Scler Relat Disord 36:101414. https://doi.org/10.1016/j.msard.2019.101414

    Article  PubMed  Google Scholar 

  23. Pawlitzki M, Horbrugger M, Loewe K, Kaufmann J, Opfer R, Wagner M, Al-Nosairy KO, Meuth SG, Hoffmann MB, Schippling S (2020) MS optic neuritis-induced long-term structural changes within the visual pathway. Neurol Neuroimmunol Neuroinflamm. https://doi.org/10.1212/NXI.0000000000000665

    Article  PubMed  PubMed Central  Google Scholar 

  24. Coric D, Balk LJ, Verrijp M, Eijlers A, Schoonheim MM, Killestein J, Uitdehaag BM, Petzold A (2018) Cognitive impairment in patients with multiple sclerosis is associated with atrophy of the inner retinal layers. Mult Scler 24(2):158–166. https://doi.org/10.1177/1352458517694090

    Article  PubMed  Google Scholar 

  25. Diamond BJ, Johnson SK, Kaufman M, Graves L (2008) Relationships between information processing, depression, fatigue and cognition in multiple sclerosis. Arch Clin Neuropsychol 23(2):189–199. https://doi.org/10.1016/j.acn.2007.10.002

    Article  PubMed  Google Scholar 

  26. Hu M, Muhlert N, Robertson N, Winter M (2019) Perceived fatigue and cognitive performance change in multiple sclerosis: uncovering predictors beyond baseline fatigue. Mult Scler Relat Disord 32:46–53. https://doi.org/10.1016/j.msard.2019.04.011

    Article  CAS  PubMed  Google Scholar 

  27. 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(8):998–1005. https://doi.org/10.1177/1352458509106213

    Article  CAS  PubMed  Google Scholar 

  28. Llufriu S, Martinez-Heras E, Solana E, Sola-Valls N, Sepulveda M, Blanco Y, Martinez-Lapiscina EH, Andorra M, Villoslada P, Prats-Galino A, Saiz A (2017) Structural networks involved in attention and executive functions in multiple sclerosis. Neuroimage Clin 13:288–296. https://doi.org/10.1016/j.nicl.2016.11.026

    Article  PubMed  Google Scholar 

  29. Ashton K, Fuchs TA, Oship D, Zivadinov R, Jakimovski D, Bergsland N, Ramasamy DP, Vaughn C, Weinstock-Guttman B, Benedict RHB, Dwyer MG (2020) Diagnosis of depression in multiple sclerosis is predicted by frontal-parietal white matter tract disruption. J Neurol. https://doi.org/10.1007/s00415-020-10110-3

    Article  PubMed  Google Scholar 

  30. Golan D, Doniger GM, Wissemann K, Zarif M, Bumstead B, Buhse M, Fafard L, Lavi I, Wilken J, Gudesblatt M (2018) The impact of subjective cognitive fatigue and depression on cognitive function in patients with multiple sclerosis. Mult Scler 24(2):196–204. https://doi.org/10.1177/1352458517695470

    Article  PubMed  Google Scholar 

  31. Chen MH, Chiaravalloti ND, Genova HM, Costa SL (2020) Visual and motor confounds on the symbol digit modalities test. Mult Scler Relat Disord 45:102436. https://doi.org/10.1016/j.msard.2020.102436

    Article  PubMed  Google Scholar 

  32. Nygaard GO, de Rodez Benavent SA, Harbo HF, Laeng B, Sowa P, Damangir S, Bernhard Nilsen K, Etholm L, Tonnesen S, Kerty E, Drolsum L, Inge Landro N, Celius EG (2015) Eye and hand motor interactions with the Symbol Digit Modalities Test in early multiple sclerosis. Mult Scler Relat Disord 4(6):585–589. https://doi.org/10.1016/j.msard.2015.08.003

    Article  PubMed  Google Scholar 

  33. Fielding J, Kilpatrick T, Millist L, White O (2009) Antisaccade performance in patients with multiple sclerosis. Cortex 45(7):900–903. https://doi.org/10.1016/j.cortex.2009.02.016

    Article  PubMed  Google Scholar 

  34. Arnett PA, Smith MM, Barwick FH, Benedict RH, Ahlstrom BP (2008) Oralmotor slowing in multiple sclerosis: relationship to neuropsychological tasks requiring an oral response. J Int Neuropsychol Soc 14(3):454–462. https://doi.org/10.1017/S1355617708080508

    Article  PubMed  Google Scholar 

  35. Liu YL, Hsieh YT, Chen TF, Chiou JM, Tsai MK, Chen JH, Chen YC (2019) Retinal ganglion cell-inner plexiform layer thickness is nonlinearly associated with cognitive impairment in the community-dwelling elderly. Alzheimers Dement (Amst) 11:19–27. https://doi.org/10.1016/j.dadm.2018.10.006

    Article  CAS  Google Scholar 

  36. Mutlu U, Colijn JM, Ikram MA, Bonnemaijer PWM, Licher S, Wolters FJ, Tiemeier H, Koudstaal PJ, Klaver CCW, Ikram MK (2018) Association of retinal neurodegeneration on optical coherence tomography with dementia: a population-based study. JAMA Neurol 75(10):1256–1263. https://doi.org/10.1001/jamaneurol.2018.1563

    Article  PubMed  PubMed Central  Google Scholar 

  37. Khawaja AP, Chan MP, Yip JL, Broadway DC, Garway-Heath DF, Luben R, Hayat S, Matthews FE, Brayne C, Khaw KT, Foster PJ (2016) Retinal nerve fiber layer measures and cognitive function in the EPIC-Norfolk Cohort Study. Investig Ophthalmol Vis Sci 57(4):1921–1926. https://doi.org/10.1167/iovs.16-19067

    Article  Google Scholar 

  38. Ko F, Muthy ZA, Gallacher J, Sudlow C, Rees G, Yang Q, Keane PA, Petzold A, Khaw PT, Reisman C, Strouthidis NG, Foster PJ, Patel PJ, Eye UKB, Vision C (2018) Association of retinal nerve fiber layer thinning with current and future cognitive decline: a study using optical coherence tomography. JAMA Neurol 75(10):1198–1205. https://doi.org/10.1001/jamaneurol.2018.1578

    Article  PubMed  PubMed Central  Google Scholar 

  39. Rovere G, Nadal-Nicolas FM, Agudo-Barriuso M, Sobrado-Calvo P, Nieto-Lopez L, Nucci C, Villegas-Perez MP, Vidal-Sanz M (2015) Comparison of retinal nerve fiber layer thinning and retinal ganglion cell loss after optic nerve transection in adult albino rats. Investig Ophthalmol Vis Sci 56(8):4487–4498. https://doi.org/10.1167/iovs.15-17145

    Article  Google Scholar 

  40. Syc SB, Saidha S, Newsome SD, Ratchford JN, Levy M, Ford E, Crainiceanu CM, Durbin MK, Oakley JD, Meyer SA, Frohman EM, Calabresi PA (2012) Optical coherence tomography segmentation reveals ganglion cell layer pathology after optic neuritis. Brain 135(Pt 2):521–533. https://doi.org/10.1093/brain/awr264

    Article  PubMed  Google Scholar 

  41. Green AJ, McQuaid S, Hauser SL, Allen IV, Lyness R (2010) Ocular pathology in multiple sclerosis: retinal atrophy and inflammation irrespective of disease duration. Brain 133(Pt 6):1591–1601. https://doi.org/10.1093/brain/awq080

    Article  PubMed  PubMed Central  Google Scholar 

  42. Jakimovski D, Bergsland N, Dwyer MG, Hagemeier J, Ramasamy DP, Szigeti K, Guttuso T, Lichter D, Hojnacki D, Weinstock-Guttman B, Benedict RHB, Zivadinov R (2020) Long-standing multiple sclerosis neurodegeneration: volumetric magnetic resonance imaging comparison to Parkinson’s disease, mild cognitive impairment, Alzheimer’s disease, and elderly healthy controls. Neurobiol Aging 90:84–92. https://doi.org/10.1016/j.neurobiolaging.2020.02.002

    Article  PubMed  PubMed Central  Google Scholar 

  43. Jakimovski D, Weinstock-Guttman B, Roy S, Jaworski M 3rd, Hancock L, Nizinski A, Srinivasan P, Fuchs TA, Szigeti K, Zivadinov R, Benedict RHB (2019) Cognitive profiles of aging in multiple sclerosis. Front Aging Neurosci 11:105. https://doi.org/10.3389/fnagi.2019.00105

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

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

    Dejan Jakimovski, Tom A. Fuchs, Niels Bergsland, Michael G. Dwyer & Robert Zivadinov

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

    Dejan Jakimovski, Ralph H. B. Benedict, Bianca Weinstock-Guttman, Osman Ozel, Tom A. Fuchs, Norah Lincoff, Niels Bergsland, Michael G. Dwyer & Robert Zivadinov

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

    Niels Bergsland

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

    Robert Zivadinov

Authors
  1. Dejan Jakimovski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ralph H. B. Benedict
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bianca Weinstock-Guttman
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Osman Ozel
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tom A. Fuchs
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Norah Lincoff
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Niels Bergsland
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Michael G. Dwyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Robert Zivadinov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dejan Jakimovski.

Ethics declarations

Conflicts of interest

Dejan Jakimovski, Niels Bergsland, Osman Ozel, Tom A Fuchs, and Norah Lincoff 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. 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, and Abbvie. Dr Weinstock-Guttman received research funds from Biogen Idec, EMD Serono, Genentech, and Novartis. 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, and V-WAVE Medical and Boston Scientific.

Ethical standard

All procedures were in accordance with the ethical standards of the institutional research board (IRB) and with the Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

All study participants signed a written consent form.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 21 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jakimovski, D., Benedict, R.H.B., Weinstock-Guttman, B. et al. Visual deficits and cognitive assessment of multiple sclerosis: confounder, correlate, or both?. J Neurol 268, 2578–2588 (2021). https://doi.org/10.1007/s00415-021-10437-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00415-021-10437-5

Keywords

Search

Navigation