Journals / Acta Medica Alanya / 2026 / Cilt: 10 Sayı: 3

Current Biomarkers in Neurology: A Clinical Perspective

Nörolojide Güncel Biyobelirteçler: Bir Klinik Bakış Açısı

Ozan Dörtkol(Istanbul Physical Therapy and Rehabilitation Education and Research Hospital, Department of Neurology)0000-0002-6152-2369
Zeynep Kara(Istanbul Physical Therapy and Rehabilitation Education and Research Hospital, Department of Neurology)0009-0007-5612-3631
Arife Çimen Atalar(Istanbul Physical Therapy and Rehabilitation Education and Research Hospital, Department of Neurology)0000-0003-0328-9607
Pages
317–322
Publication Date
2026-10-20
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Digital biomarkers and artificial intelligence-supported analyses are considered promising approaches that may contribute to clinical decision-making processes in the future.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The aim of this review is to evaluate current biomarkers in neurological diseases in terms of their diagnostic value, limitations, and relationships with each other.
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Key Findings & Data:In this narrative review, the literature published up to January 2026 was searched through PubMed and Web of Science databases.
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Conclusion & Impact:Digital biomarkers and artificial intelligence-supported analyses are considered promising approaches that may contribute to clinical decision-making processes in the future.
🔬Design:Review & Systematic Survey
📍Scope:2026 Verileri
⚙️Variables:Biyobelirteç · nöroloji · beyin omurilik sıvısı

Abstract

The aim of this review is to evaluate current biomarkers in neurological diseases in terms of their diagnostic value, limitations, and relationships with each other. In this narrative review, the literature published up to January 2026 was searched through PubMed and Web of Science databases. Current studies related to neurological diseases and biomarkers were evaluated, while non-English publications and conference abstracts were excluded. Biomarkers based on cerebrospinal fluid, neuroimaging, and physiological methods were reviewed. Cerebrospinal fluid biomarkers were found to reflect the molecular processes of diseases, whereas imaging methods reveal the spatial distribution of pathological changes. The multimodal use of biomarkers may improve diagnostic accuracy. However, the need for invasive procedures, as well as limitations related to cost and accessibility, restrict their clinical applicability. Biomarkers provide significant advantages in the early diagnosis, staging, and individualized treatment approaches of neurological diseases. Digital biomarkers and artificial intelligence-supported analyses are considered promising approaches that may contribute to clinical decision-making processes in the future.

Özet

Bu derlemenin amacı, nörolojik hastalıklardaki güncel biyobelirteçleri; tanısal değerleri ve sınırlılıkları ile birbirleriyle ilişkileri açısından değerlendirmektir. Bu derlemede literatür, Ocak 2026’ya kadar PubMed ve Web of Science veri tabanlarında taranmıştır. Nörolojik hastalıklar ve biyobelirteçlerle ilişkili güncel çalışmalar değerlendirilmiş; İngilizce dışındaki yayınlar ve kongre özetleri dahil edilmemiştir. Beyin omurilik sıvısı, nörogörüntüleme ve fizyolojik yöntemlere dayalı biyobelirteçler değerlendirilmiştir. Beyin omurilik sıvısındaki biyobelirteçlerin moleküler süreçleri, görüntüleme yöntemlerinin ise patolojik değişikliklerin mekansal dağılımını ortaya koyduğu görülmüştür. Biyobelirteçlerin multimodal kullanımı tanısal doğruluğu artırabilmektedir. Ancak bazı durumlarda invaziv girişimlerin gerekmesi, maliyet ve erişilebilirlik yetersizliği klinik kullanımda kısıtlılıklar oluşturmaktadır. Biyobelirteçler nörolojik hastalıkların erken tanısı, evrelemesi ve bireyselleştirilmiş tedavi yaklaşımları açısından önemli avantajlar sağlamaktadır. Dijital biyobelirteçler ve yapay zekâ destekli analizler, gelecekte klinik karar süreçlerine katkı sağlayabilecek umut verici yaklaşımlar olarak değerlendirilmektedir.

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Cite This Article

Dörtkol, O., Kara, Z., Atalar, A. Ç. (2026). Current Biomarkers in Neurology: A Clinical Perspective. Acta Medica Alanya, Cilt: 10 Sayı: 3, 317–322. https://doi.org/10.30565/medalanya.1919523

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References (45)

  1. Hansson O. Biomarkers for neurodegenerative diseases. Nat Med. 2021;27(6):954-63. doi: 10.1038/s41591-021-01382-x.
  2. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology. 1984;34(7):939-44. doi: 10.1212/wnl.34.7.939.
  3. Bateman RJ, Xiong C, Benzinger TL, Fagan AM, Goate A, Fox NC et al. Dominantly Inherited Alzheimer Network. Clinical and biomarker changes in dominantly inherited Alzheimer's disease. N Engl J Med. 2012;367(9):795-804. doi: 10.1056/NEJMoa1202753.
  4. Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14(4):535-62. doi: 10.1016/j.jalz.2018.02.018.
  5. Ost M, Nylén K, Csajbok L, Ohrfelt AO, Tullberg M, Wikkelsö C et al. Initial CSF total tau correlates with 1-year outcome in patients with traumatic brain injury. Neurology. 2006;67(9):1600-4. doi: 10.1212/01.wnl.0000242732.06714.0f.
  6. Sato C, Barthélemy NR, Mawuenyega KG, Patterson BW, Gordon BA, Jockel-Balsarotti J et al. Tau Kinetics in Neurons and the Human Central Nervous System. Neuron. 2018;97(6):1284-1298.e7. doi: 10.1016/j.neuron.2018.04.035.
  7. Suárez-Calvet M, Karikari TK, Ashton NJ, Lantero Rodríguez J, Milà-Alomà M, Gispert JD et al. Novel tau biomarkers phosphorylated at T181, T217 or T231 rise in the initial stages of the preclinical Alzheimer's continuum when only subtle changes in Aβ pathology are detected. EMBO Mol Med. 2020;12(12):e12921. doi: 10.15252/emmm.202012921.
  8. Johnson KA, Schultz A, Betensky RA, Becker JA, Sepulcre J, Rentz D et al. Tau positron emission tomographic imaging in aging and early Alzheimer disease. Ann Neurol. 2016;79(1):110-9. doi: 10.1002/ana.24546.
  9. Hill DLG, Schwarz AJ, Isaac M, Pani L, Vamvakas S, Hemmings R et al. Coalition Against Major Diseases/European Medicines Agency biomarker qualification of hippocampal volume for enrichment of clinical trials in predementia stages of Alzheimer's disease. Alzheimers Dement. 2014;10(4):421-429.e3. doi: 10.1016/j.jalz.2013.07.003.
  10. Gordon BA, Friedrichsen K, Brier M, Blazey T, Su Y, Christensen J, Aldea P et al. The relationship between cerebrospinal fluid markers of Alzheimer pathology and positron emission tomography tau imaging. Brain. 2016;139(Pt 8):2249-60. doi: 10.1093/brain/aww139.
  11. Benvenutto A, Giusiano B, Koric L, Gueriot C, Didic M, Felician O et al. Imaging Biomarkers of Neurodegeneration in Alzheimer's Disease: Distinct Contributions of Cortical MRI Atrophy and FDG-PET Hypometabolism. J Alzheimers Dis. 2018;65(4):1147-57. doi: 10.3233/JAD-180292.
  12. Milà-Alomà M, Salvadó G, Gispert JD, Vilor-Tejedor N, Grau-Rivera O, Sala-Vila A et al. Amyloid beta, tau, synaptic, neurodegeneration, and glial biomarkers in the preclinical stage of the Alzheimer's continuum. Alzheimers Dement. 2020;16(10):1358-1371. doi: 10.1002/alz.12131.
  13. Knopman DS, Jack CR Jr, Wiste HJ, Weigand SD, Vemuri P, Lowe VJ et al. Age and neurodegeneration imaging biomarkers in persons with Alzheimer disease dementia. Neurology. 2016;87(7):691-8. doi: 10.1212/WNL.0000000000002979.
  14. Liguori C, Mercuri NB, Izzi F, Romigi A, Cordella A, Sancesario G et al. Obstructive Sleep Apnea is Associated With Early but Possibly Modifiable Alzheimer's Disease Biomarkers Changes. Sleep. 2017;40(5). doi: 10.1093/sleep/zsx011.
  15. Ooms S, Overeem S, Besse K, Rikkert MO, Verbeek M, Claassen JA. Effect of 1 night of total sleep deprivation on cerebrospinal fluid β-amyloid 42 in healthy middle-aged men: a randomized clinical trial. JAMA Neurol. 2014;71(8):971-7. doi: 10.1001/jamaneurol.2014.1173.
  16. Af Bjerkén S, Axelsson J, Larsson A, Flygare C, Remes J, Strandberg S et al. Reliability and validity of visual analysis of [ 18 F]FE-PE2I PET/CT in early Parkinsonian disease. Nucl Med Commun. 2023;44(5):397-406. doi: 10.1097/MNM.0000000000001679.
  17. Morbelli S, Esposito G, Arbizu J, Barthel H, Boellaard R, Bohnen NI et al. EANM practice guideline/SNMMI procedure standard for dopaminergic imaging in Parkinsonian syndromes 1.0. Eur J Nucl Med Mol Imaging. 2020;47(8):1885-912. doi: 10.1007/s00259-020-04817-8.
  18. Arena JE, Stoessl AJ. Optimizing diagnosis in Parkinson's disease: Radionuclide imaging. Parkinsonism Relat Disord. 2016;22 Suppl 1:S47-51. doi: 10.1016/j.parkreldis.2015.09.029.
  19. Hellwig S, Amtage F, Kreft A, Buchert R, Winz OH, Vach W et al. [¹⁸F]FDG-PET is superior to [¹²³I]IBZM-SPECT for the differential diagnosis of parkinsonism. Neurology. 2012;79(13):1314-22. doi: 10.1212/WNL.0b013e31826c1b0a.
  20. Ton TG, Jain S, Biggs ML, Thacker EL, Strotmeyer ES, Boudreau R et al. Markers of inflammation in prevalent and incident Parkinson's disease in the Cardiovascular Health Study. Parkinsonism Relat Disord. 2012;18(3):274-8. doi: 10.1016/j.parkreldis.2011.11.003.
  21. Carli G, Caminiti SP, Galbiati A, Marelli S, Casoni F, Padovani A et al. In-vivo signatures of neurodegeneration in isolated rapid eye movement sleep behaviour disorder. Eur J Neurol. 2020;27(7):1285-95. doi: 10.1111/ene.14215.
  22. Owens E, Krecke K, Ahlskog JE, Fealey R, Hassan A, Josephs KA et al. Highly specific radiographic marker predates clinical diagnosis in progressive supranuclear palsy. Parkinsonism Relat Disord. 2016;28:107-11. doi: 10.1016/j.parkreldis.2016.05.006.
  23. Mahlknecht P, Hotter A, Hussl A, Esterhammer R, Schocke M, Seppi K. Significance of MRI in diagnosis and differential diagnosis of Parkinson's disease. Neurodegener Dis. 2010;7(5):300-18. doi: 10.1159/000314495.
  24. Keir G, Roytman M, Mashriqi F, Shahsavarani S, Franceschi AM. Atypical Parkinsonian Syndromes: Structural, Functional, and Molecular Imaging Features. AJNR Am J Neuroradiol. 2024;45(12):1865-77. doi: 10.3174/ajnr.A8313.
  25. Coughlin DG, Hurtig HI, Irwin DJ. Pathological Influences on Clinical Heterogeneity in Lewy Body Diseases. Mov Disord. 2020;35(1):5-19. doi: 10.1002/mds.27867.
  26. Mena AM, Strafella AP. Imaging pathological tau in atypical parkinsonisms: A review. Clin Park Relat Disord. 2022;7:100155. doi: 10.1016/j.prdoa.2022.100155.
  27. Hansson O, Janelidze S, Hall S, Magdalinou N, Lees AJ, Andreasson U et al. Swedish BioFINDER study. Blood-based NfL: A biomarker for differential diagnosis of parkinsonian disorder. Neurology. 2017;88(10):930-937. doi: 10.1212/WNL.0000000000003680.
  28. Gibbons C, Wang N, Rajan S, Kern D, Palma JA, Kaufmann H et al. Cutaneous α-Synuclein Signatures in Patients With Multiple System Atrophy and Parkinson Disease. Neurology. 2023;100(15):e1529-39. doi: 10.1212/WNL.0000000000207614.
  29. Seelaar H, Rohrer JD, Pijnenburg YA, Fox NC, van Swieten JC. Clinical, genetic and pathological heterogeneity of frontotemporal dementia: a review. J Neurol Neurosurg Psychiatry. 2011;82(5):476-86. doi: 10.1136/jnnp.2010.212225.
  30. Palmqvist S, Janelidze S, Quiroz YT, Zetterberg H, Lopera F, Stomrud E et al. Discriminative Accuracy of Plasma Phospho-tau217 for Alzheimer Disease vs Other Neurodegenerative Disorders. JAMA. 2020;324(8):772-81. doi: 10.1001/jama.2020.12134.
  31. Woollacott IOC, Nicholas JM, Heller C, Foiani MS, Moore KM, Russell LL et al. Cerebrospinal Fluid YKL-40 and Chitotriosidase Levels in Frontotemporal Dementia Vary by Clinical, Genetic and Pathological Subtype. Dement Geriatr Cogn Disord. 2020;49(1):56-76. doi: 10.1159/000506282.
  32. Schmitz M, Cramm M, Llorens F, Müller-Cramm D, Collins S, Atarashi R et al. The real-time quaking-induced conversion assay for detection of human prion disease and study of other protein misfolding diseases. Nat Protoc. 2016;11(11):2233-2242. doi: 10.1038/nprot.2016.120.
  33. Boesenberg-Grosse C, Schulz-Schaeffer WJ, Bodemer M, Ciesielczyk B, Meissner B, Krasnianski A, et al. Brain-derived proteins in the CSF: do they correlate with brain pathology in CJD? BMC Neurol. 2006;6:35. doi: 10.1186/1471-2377-6-35.
  34. Leurs CE, Twaalfhoven H, Lissenberg-Witte BI, van Pesch V, Dujmovic I, Drulovic J et al. Kappa free light chains is a valid tool in the diagnostics of MS: A large multicenter study. Mult Scler. 2020;26(8):912-923. doi: 10.1177/1352458519845844.
  35. Galetta KM, Calabresi PA, Frohman EM, Balcer LJ. Optical coherence tomography (OCT): imaging the visual pathway as a model for neurodegeneration. Neurotherapeutics. 2011;8(1):117-32. doi: 10.1007/s13311-010-0005-1.
  36. Kläppe U, Sennfält S, Lovik A, Finn A, Bofaisal U, Zetterberg H et al. Neurodegenerative biomarkers outperform neuroinflammatory biomarkers in amyotrophic lateral sclerosis. Amyotroph Lateral Scler Frontotemporal Degener. 2024;25(1-2):150-61. doi: 10.1080/21678421.2023.2263874.
  37. Hohenfeld C, Werner CJ, Reetz K. Resting-state connectivity in neurodegenerative disorders: Is there potential for an imaging biomarker? Neuroimage Clin. 2018;18:849-70. doi: 10.1016/j.nicl.2018.03.013.
  38. Ossenkoppele R, van der Kant R, Hansson O. Tau biomarkers in Alzheimer's disease: towards implementation in clinical practice and trials. Lancet Neurol. 2022;21(8):726-34. doi: 10.1016/S1474-4422(22)00168-5.
  39. Park SA, Han SM, Kim CE. New fluid biomarkers tracking non-amyloid-β and non-tau pathology in Alzheimer's disease. Exp Mol Med. 2020;52(4):556-68. doi: 10.1038/s12276-020-0418-9
  40. Pellegrini E, Ballerini L, Hernandez MDCV, Chappell FM, González-Castro V, Anblagan D et al. Machine learning of neuroimaging for assisted diagnosis of cognitive impairment and dementia: A systematic review. Alzheimers Dement (Amst). 2018;10:519-535. doi: 10.1016/j.dadm.2018.07.004.
  41. Zuo XN, Xing XX. Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: a systems neuroscience perspective. Neurosci Biobehav Rev. 2014;45:100-18. doi: 10.1016/j.neubiorev.2014.05.009.
  42. Basaia S, Agosta F, Wagner L, Canu E, Magnani G, Santangelo R et al. Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks. Neuroimage Clin. 2019;21:101645. doi: 10.1016/j.nicl.2018.101645.
  43. Budd Haeberlein S, Aisen PS, Barkhof F, Chalkias S, Chen T, Cohen S et al. Two Randomized Phase 3 Studies of Aducanumab in Early Alzheimer's Disease. J Prev Alzheimers Dis. 2022;9(2):197-210. doi: 10.14283/jpad.2022.30.
  44. Altuna-Azkargorta M, Mendioroz-Iriarte M. Blood biomarkers in Alzheimer's disease. Neurologia (Engl Ed). 2021;36(9):704-710. doi:10.1016/j.nrleng.2018.03.006.
  45. Bonanno M, Ielo A, De Pasquale P, Celesti A, De Nunzio AM, Quartarone A et al. Use of Wearable Sensors to Assess Fall Risk in Neurological Disorders: Systematic Review. JMIR Mhealth Uhealth. 2025;13:e67265. doi: 10.2196/67265.