Biochemical markers of neurodegeneration in patients with cerebral small vessel disease and Alzheimer's disease

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Abstract

Introduction. Cerebral small vessel disease (CSVD) as well as the Alzheimer's disease (AD) and their comorbidities are the most common causes of cognitive impairments (CIs).

Objective: to evaluate the predictive power of the biochemical neurodegeneration markers in patients with CSVD and AD.

Materials and methods. We assessed the following neurodegeneration markers in 68 patients with CSVD (61.0 ± 8.6 years; 60.3% males), 17 patients with AD (65.2 ± 8.3 years; 35.3% males), and 26 healthy volunteers (59.9 ± 6.7 years; 38.5% males): neuron-specific enolase (NSE), glial fibrillary acid protein (GFAP), neurofilament light polypeptide (NEFL) in blood (for all patients) and in cerebrospinal fluid (CSF; in patients with CSVD and AD). We assessed the predictive power of those markers with ROC analysis.

Results. As compared to the control group, serum GFAP in patients with CSVD showed its predictive power at 0.155 ng/ml (sensitivity 74%; specificity 70%). Serum NEFL > 0.0185 ng/ml (sensitivity 82%; specificity 96%) and NSE < 4.95 μg/ml (sensitivity 77%; specificity 71%) showed their predictive power in patients with AD. CSF GFAP > 1.03 ng/ml (sensitivity 84%; specificity 88%), CSF NSE < 19.10 μg/ml (sensitivity 88%; specificity 91%), serum NEFL < 0.021 ng/ml (sensitivity 71%; specificity 76%), serum NSE /CSF NSE ratio > 0.273 ng/ml (sensitivity 87%; specificity 88%) help differentiate CSVD from AD.

Conclusions. We found that serum GFAP can be a useful diagnostic marker in patients with CSVD, while serum NEFL and serum NSE can help identify the AD. In addition, CSF GFAP and CSF NSE as well as serum NEFL and serum NSE/CSF NSE can help differentiate CSVD from AD. We can use those markers in clinical and research practice to identify the vascular and neurodegenerative causes of CIs and their comorbidities, which is of a great importance in developing specific treatment and predicting the course of the disease.

About the authors

Larisa A. Dobrynina

Research Center of Neurology

Email: dobrla@mail.ru
ORCID iD: 0000-0001-9929-2725

D. Sci. (Med.), chief researcher, Head, 3rd Neurological department, Institute of Clinical and Preventive Neurology, Research Center of Neurology, Moscow, Russia

Russian Federation, Moscow

Maria M. Tsypushtanova

Research Center of Neurology

Email: tzipushtanova@mail.ru
ORCID iD: 0000-0002-4231-3895

postgraduate student, neurologist, 3rd Neurological department, Institute of Clinical and Preventive Neurology, Research Center of Neurology, Moscow, Russia

Russian Federation, Moscow

Аlla A. Shabalina

Research Center of Neurology

Email: ashabalina@yandex.ru
ORCID iD: 0000-0001-9604-7775

D. Sci. (Med.), leading researcher, Head, Department of laboratory diagnostics, Research Center of Neurology, Moscow, Russia

Russian Federation, Moscow

Kamila V. Shamtieva

Research Center of Neurology

Email: kamila.shamt@gmail.com
ORCID iD: 0000-0002-6995-1352

Cand. Sci. (Med.), researcher, 3rd Neurological department, Institute of Clinical and Preventive Neurology, Research Center of Neurology, Moscow, Russia

Russian Federation, Moscow

Angelina G. Makarova

Research Center of Neurology

Email: angelinagm@mail.ru
ORCID iD: 0000-0001-8862-654X

postgraduate student, neurologist, 3rd Neurological department, Institute of Clinical and Preventive Neurology, Research Center of Neurology, Moscow, Russia

Russian Federation, Moscow

Viktoria V. Trubitsyna

Research Center of Neurology

Email: pobeda-1994@mail.ru
ORCID iD: 0000-0001-7898-6541

postgraduate student, radiologist, Department of radiation diagnostics, Research Center of Neurology, Moscow, Russia

Russian Federation, Moscow

Elina T. Bitsieva

Research Center of Neurology

Email: elinabitsieva1997@mail.ru
ORCID iD: 0000-0003-1464-0722

postgraduate student, neurologist, 3rd Neurological department, Institute of Clinical and Preventive Neurology, Research Center of Neurology, Moscow, Russia

Russian Federation, Moscow

Aleksandra A. Byrochkina

Research Center of Neurology

Email: byrochkinasasha@mail.ru
ORCID iD: 0000-0002-2285-2533

postgraduate student, neurologist, 3rd Neurological department, Institute of Clinical and Preventive Neurology, Research Center of Neurology, Moscow, Russia

Russian Federation, Moscow

Anastasia A. Geints

Lomonosov Moscow State University

Author for correspondence.
Email: anastasiyatarasova75@gmail.com
ORCID iD: 0009-0001-1836-2515

resident of the 6rd neurological department of the Research Center of Neurology

Russian Federation, Moscow

References

  1. Gorelick P.B., Scuteri A., Black S.E. et al. Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the american heart association/american stroke association. Stroke. 2011;42:2672–2713. doi: 10.1161/STR.0b013e3182299496
  2. Wardlaw J.M., Smith E.E., Biessels G.J. et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol. 2013;12(8):822–838. doi: 10.1016/S1474-4422(13)70124-8
  3. Sachdev P., Kalaria R., O’Brien J. et al. Diagnostic criteria for vascular cognitive disorders: A VASCOG statement. Alzheimer Dis. Assoc. Disord. 2014;28(3):206–218. doi: 10.1097/WAD.0000000000000034
  4. Albert M.S., Jack C.R. Jr., Knopman D.S. et al. Introduction to the re- commendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):257–262. doi: 10.1016/j.jalz.2011.03.004
  5. McKhann G.M., Knopman D.S., Chertkow H. et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging and the Alzheimer’s Association workgroup. Alzheimers Dement. 2011;7:263–269. doi: 10.1016/j.jalz.2011.03.005.
  6. Pantoni L. Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges. Lancet Neurol. 2010;9(7):689–701. doi: 10.1016/S1474-4422(10)70104-6
  7. Holmes C., Boche D., Wilkinson D. et al. Long-term effects of Abeta42 immunisation in Alzheimer’s disease: follow-up of a randomised, placebo-controlled phase I trial. Lancet. 2008;372(9634):216–223. doi: 10.1016/S0140-6736(08)61075-2
  8. Nicoll J.A.R., Buckland G.R., Harrison C.H. et al. Persistent neuropatholo- gical effects 14 years following amyloid-β immunization in Alzheimer’s disease. Brain. 2019;142(7):2113–2126. doi: 10.1093/brain/awz142.
  9. Добрынина Л.А., Гаджиева З.Ш., Кремнева Е.И. и др. Выживаемость, изменения когнитивных функций и состояния головного мозга у пациентов с церебральной микроангиопатией (болезнью мелких сосудов): 5-летнее наблюдение. Анналы клинической и экспериментальной неврологии. 2022;16(4):18–28. Dobrynina L.A., Gadzhieva Z.Sh., Kremneva E.I. et al. Survival, cognitive functions, and brain MRI in patients with cSVD: 5-year observation. Annals of clinical and experimental neurology. 2022;16(4):18–28. doi: 10.54101/ACEN.2022.4.3
  10. Attems J., Jellinger K.A. The overlap between vascular disease and Alzheimer’s disease — lessons from pathology. BMC Med. 2014;12:206. doi: 10.1186/S12916-014-0206-2
  11. Toledo J.B., Arnold S.E., Raible K. et al. Contribution of cerebrovascular disease in autopsy confirmed neurodegenerative disease cases in the National Alzheimer’s Coordinating Centre. Brain. 2013;36(Pt 9):2697–2706. doi: 10.1093/brain/awt188
  12. Kapasi A., DeCarli C., Schneider J.A. Impact of multiple pathologies on the threshold for clinically overt dementia. Acta Neuropathol. 2017;134(2):171–186. doi: 10.1007/s00401-017-1717-7
  13. Wallin A., Kapaki E., Boban M. et al. Biochemical markers in vascular cognitive impairment associated with subcortical small vessel disease — a consensus report. BMC Neurol. 2017;17(1):102. doi: 10.1186/s12883-017-0877-3
  14. Dobrynina L.A., Shabalina A.A., Zabitova M.R. et al. Tissue plasminogen activator and MRI signs of cerebral small vessel disease. Brain Sci. 2019;9(10):266. doi: 10.3390/brainsci9100266
  15. Garwood C.J., Ratcliffe L.E., Simpson J.E. et al. Review: astrocytes in Alzheimer’s disease and other age-associated dementias: a supporting player with a central role. Neuropathol. Appl. Neurobiol. 2017;43(4):281–298. doi: 10.1111/nan.12338
  16. Oeckl P., Halbgebauer S., Anderl-Straub S. et al. Glial fibrillary acidic protein in serum is increased in Alzheimer’s disease and correlates with cognitive impairment. J. Alzheimers Dis. 2019;67(2):481–488. doi: 10.3233/JAD-180325
  17. Plog B.A., Dashnaw M.L., Hitomi E. et al. Biomarkers of traumatic injury are transported from brain to blood via the glymphatic system. J. Neurosci. 2015;35(2):518–526. doi: 10.1523/JNEUROSCI.3742-14.2015
  18. Sharquie I.K., Gawwam G.A., Abdullah S.F. Serum glial fibrillary acidic protein: a surrogate marker of the activity of multiple sclerosis. Medeni Med. J. 2020;35(3):212–218. doi: 10.5222/MMJ.2020.48265
  19. Elahi F.M., Casaletto K.B., La Joie R. et al. Plasma biomarkers of astrocytic and neuronal dysfunction in early- and late-onset Alzheimer’s disease. Alzheimer’s Dement. 2020;16(4):681–695. doi: 10.1016/j.jalz.2019.09.004
  20. Jesse S., Steinacker P., Cepek L. et al. Glial fibrillary acidic protein and protein S-100B: different concentration pattern of glial proteins in cerebrospinal fluid of patients with Alzheimer’s disease and Creutzfeldt–Jakob disease. J. Alzheimers Dis. 2009;17(3):541–551. doi: 10.3233/JAD-2009-1075
  21. Cicognola C., Janelidze S., Hertze J. et al. Plasma glial fibrillary acidic protein detects Alzheimer pathology and predicts future conversion to Alzheimer dementia in patients with mild cognitive impairment. Alzheimer’s Res. Ther. 2021;13(1):1–9. doi: 10.1186/s13195-021-00804-9
  22. Thijssen E.H., Verberk I.M.W., Stoops E. et al. Amyloid, pTau, NfL, and GFAP as biomarkers for Alzheimer’s disease. Alzheimer’s Dement. 2020;16(S5):38179. doi: 10.1002/alz.038179
  23. Chatterjee P., Pedrini S., Stoops E. et al. Plasma glial fibrillary acidic protein is elevated in cognitively normal older adults at risk of Alzheimer’s disease. Transl. Psychiatry. 2021;11(1):1–10. doi: 10.1038/s41398-020-01137-1
  24. Karikari T.K., Hourregue C., Cognat E. et al. Differences between plasma and cerebrospinal fluid glial fibrillary acidic protein levels across the Alzheimer disease continuum. JAMA Neurol. 2021;78(12):1471–1483. doi: 10.1001/jamaneurol.2021.3671
  25. Pereira J.B., Janelidze S., Smith R. et al. Plasma GFAP is an early marker of amyloid-β but not tau pathology in Alzheimer’s disease. Brain. 2021;144(11):3505–3516. doi: 10.1093/brain/awab223
  26. Verberk I.M.W., Laarhuis M.B., van den Bosch K.A. et al. Serum markers glial fibrillary acidic protein and neurofilament light for prognosis and monitoring in cognitively normal older people: a prospective memory clinic-based cohort study. Lancet Healthy Longev. 2021;2(2):E87–E95. doi: 10.1016/S2666-7568(20)30061-1
  27. Shir D., Graff-Radford J., Hofrenning E.I. et al. Association of plasma glial fibrillary acidic protein (GFAP) with neuroimaging of Alzheimer’s disease and vascular pathology. Alzheimers Dement. (Amst). 2022;14(1):e12291. doi: 10.1002/dad2.12291
  28. Amalia L. Glial fibrillary acidic protein (GFAP): Neuroinflammation biomarker in acute ischemic stroke. J. Inflamm. Res. 2021;14:7501–7506. doi: 10.2147/JIR.S342097
  29. Puspitasari V., Gunawan P.Y., Wiradarma H.D. et al. Glial fibrillary acidic protein serum level as a predictor of clinical outcome in ischemic stroke. Open Access Maced J Med Sci. 2019;7(9):1471–1474. doi: 10.3889/oamjms.2019.326
  30. Huss A., Abdelhak A., Mayer B. et al. Association of serum GFAP with functional and neurocognitive outcome in sporadic small vessel disease. Biomedicines. 2022;10(8):1869. doi: 10.3390/biomedicines10081869
  31. Katayama T., Sawada J., Takahashi K. et al. Meta-analysis of cerebrospinal fluid neuron-specific enolase levels in Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies, and multiple system atrophy. Alzheimers Res. Therapy. 2021;13(1):163. doi: 10.1186/s13195-021-00907-3
  32. Olsson B., Lautner R., Andreasson U. et al. CSF and blood biomarkers for the diagnosis of Alzheimer’s disease: a systematic review and meta-analysis. Lancet Neurol. 2016;15(7):673–684. doi: 10.1016/S1474-4422(16)00070-3
  33. Schmidt F.M., Mergl R., Stach B. et al. Elevated levels of cerebrospinal fluid neuron-specific enolase (NSE) in Alzheimer’s disease. Neurosci. Lett. 2014;570:81–85. doi: 10.1016/j.neulet.2014.04.007
  34. Palumbo B., Siepi D., Sabalich I. et al. Cerebrospinal fluid neuron-speci- fic enolase: a further marker of Alzheimer’s disease? Funct. Neurol. 2008;23(2): 93–96.
  35. Wallin A., Blennow K., Rosengren L. Cerebrospinal fluid markers of pathogenetic processes in vascular dementia, with special reference to the subcortical subtype. Alzheimer Dis. Assoc. Disord. 1999;13(Suppl 3):S102–S105.
  36. González-Quevedo A., García S.G., Concepción O.F. et al. Increased serum S-100B and neuron specific enolase — Potential markers of early nervous system involvement in essential hypertension. Clin. Biochem. 2011;44(2–3):154–159. doi: 10.1016/j.clinbiochem.2010.11.006
  37. Polyakova M., Mueller K., Arelin K. et al. Increased serum NSE and S100B indicate neuronal and glial alterations in subjects under 71 Years with mild neurocognitive disorder/mild cognitive impairment. Front. Cell Neurosci. 2022;16:788150. doi: 10.3389/fncel.2022.788150
  38. Perrot R., Berges R., Bocquet A. et al. Review of the multiple aspects of neurofilament functions, and their possible contribution to neurodegeneration. Mol. Neurobiol. 2008;38(1):27–65. doi: 10.1007/s12035-008-8033-0
  39. Mattsson N., Andreasson U., Zetterberg H. et al. Association of plasma neurofilament light with neurodegeneration in patients with Alzheimer disease. JAMA Neurol. 2017;74(5):557–566. doi: 10.1001/jamaneurol.2016.6117
  40. de Wolf F., Ghanbari M., Licher S. et al. Plasma tau, neurofilament light chain and amyloid-β levels and risk of dementia; a population-based cohort study. Brain. 2020;143(4):1220–1232. doi: 10.1093/brain/awaa054
  41. Egle M., Loubiere L., Maceski A. et al. Neurofilament light chain predicts future dementia risk in cerebral small vessel disease. J. Neurol. Neurosurg. Psychiatry. 2021;92(6):582–589. doi: 10.1136/jnnp-2020-325681
  42. Ma W., Zhang J., Xu J. et al. Elevated levels of serum neurofilament light chain associated with cognitive impairment in vascular dementia. Dis. Markers. 2020;2020:6612871. doi: 10.1155/2020/6612871
  43. Jonsson M., Zetterberg H., van Straaten E. et al. Cerebrospinal fluid biomarkers of white matter lesions — cross-sectional results from the LADIS study. Eur. J. Neurol. 2010;17(3):377–382. doi: 10.1111/j.1468-1331.2009.02808.x
  44. Bjerke M., Zetterberg H., Edman Å. et al. Cerebrospinal fluid matrix metalloproteinases and tissue inhibitor of metalloproteinases in combination with subcortical and cortical biomarkers in vascular dementia and Alzheimer’s disease. J. Alzheimers Dis. 2011;27(3):665–676. doi: 10.3233/JAD-2011-110566
  45. Skillback T., Farahmand B., Bartlett J.W. et al. CSF neurofilament light differs in neurodegenerative diseases and predicts severity and survival. Neurology. 2014.83(21):1945–1953. doi: 10.1212/wnl.00000000000010
  46. Rosenberg G.A., Wallin A., Wardlaw J.M. et al. Consensus statement for diagnosis of subcortical small vessel disease. J. Cereb. Blood Flow Metab. 2016;36(1):6–25. doi: 10.1038/jcbfm.2015.172
  47. Nasreddine Z.S., Phillips N.A., Bédirian V. et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J. Am. Geriatr. Soc. 2005;53(4):695–699. doi: 10.1111/j.1532-5415.2005.53221.x
  48. Добрынина Л.А., Гаджиева З.Ш., Калашникова Л.А. и др. Нейропсихологический профиль и факторы сосудистого риска у больных с церебральной микроангиопатией. Анналы клинической и экспериментальной неврологии. 2018;12(4):5–15. Dobrynina L.A., Gadzhieva Z.Sh., Kalashnikova L.A. et al. Neuropsychological profile and vascular risk factors in patients with cerebral microangiopathy. Annals of clinical and experimental neurology. 2018;12(4):5–15. doi: 10.25692/ACEN.2018.4.1
  49. Zigmond A.S., Snaith R.P. The hospital anxiety and depression scale. Acta Psychiatr. Scand. 1983;67(6):361–370. doi: 10.1111/j.1600-0447.1983.tb09716.x

Supplementary files

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1. JATS XML
2. Fig. 1. The levels of neurodegeneration markers in patients with CSVD/AD and the control group.

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3. Fig. 2. ROC curve for serum GFAP in patients with CSVD vs the control group.

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4. Fig. 3. ROC curves for serum NEFL (А) and serum NSE (B) in patients with AD vs the control group.

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5. Fig. 4. ROC curves for serum NEFL (А), CSF NSE (B), CSF GFAP(C), serum NSE/CSF NSE (D) in patients with CSVD and AD.

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Copyright (c) 2023 Dobrynina L.A., Tsypushtanova M.M., Shabalina А.A., Shamtieva K.V., Makarova A.G., Trubitsyna V.V., Bitsieva E.T., Byrochkina A.A., Geints A.A.

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