Skip to main content

Advertisement

SpringerLink
Log in

Blood-based biomarkers in Alzheimer’s disease: a mini-review

  • Review Article
  • Published:
Metabolic Brain Disease Aims and scope Submit manuscript

Abstract

Alzheimer’s disease (AD) is the most common cause of dementia and has far reaching consequences for patients and their caregivers. Early detection and treatment are key factors in limiting the impact of the disease. However, a definitive diagnosis of AD requires an examination of brain tissue during an autopsy. Although a plethora of biomarkers such as neuroimaging, electrophysiological, and cerebrospinal fluid (CSF) biomarkers are available, their utility is limited to research due to their poor reach and prohibitive cost. In order for biomarkers to be widely used, they need to be accessible, affordable, and conducive for the patient population or disease stage. Blood-based biomarkers may not only be less expensive and more accessible compared to neuroimaging or CSF tests, but they are also preferred by patients with AD as they are much less invasive. In this mini-review article, we expand on the rationale for the use of blood-based biomarkers, review currently available biomarkers and discuss the need for the standardization of these biomarkers. We contrast the blood-based biomarkers with other available biomarkers and discuss the advantages of using a panel of blood-based biomarkers to strengthen their accuracy.

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

Similar content being viewed by others

Data availability

Not applicable

Code availability

Not applicable

References

  • Benedet AL, Mila-Aloma M, Vrillon A, Ashton NJ, Pascoal TA, Lussier F, . . ., BioCogBank Paris Lariboisiere c (2021) Differences between plasma and cerebrospinal fluid glial fibrillary acidic protein levels across the alzheimer disease continuum. JAMA Neurol 78(12): 1471–1483. https://doi.org/10.1001/jamaneurol.2021.3671

  • Biomarkers Definitions Working, G (2001) Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 69(3):89–95. https://doi.org/10.1067/mcp.2001.113989

    Article  Google Scholar 

  • Blennow K, Zetterberg H (2015) The past and the future of Alzheimer’s disease CSF biomarkers-a journey toward validated biochemical tests covering the whole spectrum of molecular events. Front Neurosci 9:345. https://doi.org/10.3389/fnins.2015.00345

    Article  Google Scholar 

  • Calzetti S, Bortone E, Negrotti A, Zinno L, Mancia D (2002) Frontal intermittent rhythmic delta activity (FIRDA) in patients with dementia with Lewy bodies: a diagnostic tool? Neurol Sci 23(Suppl 2):S65-66. https://doi.org/10.1007/s100720200072

    Article  Google Scholar 

  • Chen YR, Liang CS, Chu H, Voss J, Kang XL, O'Connell G, . . ., Chou KR (2021) Diagnostic accuracy of blood biomarkers for Alzheimer's disease and amnestic mild cognitive impairment: a meta-analysis. Ageing Res Rev 71: 101446. https://doi.org/10.1016/j.arr.2021.101446

  • Cummings J, Aisen P, Lemere C, Atri A, Sabbagh M, Salloway S (2021) Aducanumab produced a clinically meaningful benefit in association with amyloid lowering. Alzheimers Res Ther 13(1):98. https://doi.org/10.1186/s13195-021-00838-z

    Article  Google Scholar 

  • de Waal H, Stam CJ, Blankenstein MA, Pijnenburg YA, Scheltens P, van der Flier WM (2011) EEG abnormalities in early and late onset Alzheimer’s disease: understanding heterogeneity. J Neurol Neurosurg Psychiatry 82(1):67–71. https://doi.org/10.1136/jnnp.2010.216432

    Article  Google Scholar 

  • Dhiman K, Gupta VB, Villemagne VL, Eratne D, Graham PL, Fowler C, . . ., Martins RN (2020) Cerebrospinal fluid neurofilament light concentration predicts brain atrophy and cognition in Alzheimer's disease. Alzheimers Dement (Amst) 12(1): e12005. https://doi.org/10.1002/dad2.12005

  • Duits FH, Martinez-Lage P, Paquet C, Engelborghs S, Lleo A, Hausner L, . . ., Blennow K (2016) Performance and complications of lumbar puncture in memory clinics: Results of the multicenter lumbar puncture feasibility study. Alzheimers Dement 12(2): 154–163. https://doi.org/10.1016/j.jalz.2015.08.003

  • Gouw AA, Alsema AM, Tijms BM, Borta A, Scheltens P, Stam CJ, van der Flier WM (2017) EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive subjects. Neurobiol Aging 57:133–142. https://doi.org/10.1016/j.neurobiolaging.2017.05.017

    Article  Google Scholar 

  • Honig LS, Vellas B, Woodward M, Boada M, Bullock R, Borrie M, . . ., Siemers E (2018) Trial of solanezumab for mild dementia due to Alzheimer's disease. N Engl J Med 378(4): 321–330. https://doi.org/10.1056/NEJMoa1705971

  • Hull M, Berger M, Volk B, Bauer J (1996) Occurrence of interleukin-6 in cortical plaques of Alzheimer’s disease patients may precede transformation of diffuse into neuritic plaques. Ann N Y Acad Sci 777:205–212. https://doi.org/10.1111/j.1749-6632.1996.tb34420.x

    Article  CAS  Google Scholar 

  • Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, . . ., Contributors (2018) NIA-AA Research Framework: toward a biological definition of Alzheimer's disease. Alzheimers Dement 14(4): 535–562. https://doi.org/10.1016/j.jalz.2018.02.018

  • Jack CR Jr, Petersen RC, Xu YC, O'Brien PC, Smith GE, Ivnik RJ, . . ., Kokmen E (1999) Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment. Neurology 52(7): 1397–1403. https://doi.org/10.1212/wnl.52.7.1397

  • Jansen WJ, Janssen O, Tijms BM, Vos SJB, Ossenkoppele R, Visser PJ, . . ., Zetterberg H (2022) prevalence estimates of amyloid abnormality across the Alzheimer disease clinical spectrum. JAMA Neurol. https://doi.org/10.1001/jamaneurol.2021.5216

  • Kemppainen NM, Aalto S, Wilson IA, Nagren K, Helin S, Bruck A, . . ., Rinne JO (2007) PET amyloid ligand [11C]PIB uptake is increased in mild cognitive impairment. Neurology 68(19): 1603–1606. https://doi.org/10.1212/01.wnl.0000260969.94695.56

  • Keshavan A, Pannee J, Karikari TK, Rodriguez JL, Ashton NJ, Nicholas JM, . . ., Schott JM (2021) Population-based blood screening for preclinical Alzheimer's disease in a British birth cohort at age 70. Brain 144(2): 434–449. https://doi.org/10.1093/brain/awaa403

  • Kirmess KM, Meyer MR, Holubasch MS, Knapik SS, Hu Y, Jackson EN, . . ., Contois JH (2021) The PrecivityAD test: accurate and reliable LC-MS/MS assays for quantifying plasma amyloid beta 40 and 42 and apolipoprotein E proteotype for the assessment of brain amyloidosis. Clin Chim Acta 519: 267–275. https://doi.org/10.1016/j.cca.2021.05.011

  • Koenig AM, Nobuhara CK, Williams VJ, Arnold SE (2018) Biomarkers in Alzheimer’s, frontotemporal, lewy body, and vascular dementias. Focus (am Psychiatr Publ) 16(2):164–172. https://doi.org/10.1176/appi.focus.20170048

    Article  Google Scholar 

  • Kwon HS, Koh SH (2020) Neuroinflammation in neurodegenerative disorders: the roles of microglia and astrocytes. Transl Neurodegener 9(1):42. https://doi.org/10.1186/s40035-020-00221-2

    Article  Google Scholar 

  • Landau SM, Harvey D, Madison CM, Koeppe RA, Reiman EM, Foster NL, . . ., Alzheimer's Disease Neuroimaging, I (2011) Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiol Aging 32(7): 1207–1218. https://doi.org/10.1016/j.neurobiolaging.2009.07.002

  • Leuzy A, Smith R, Cullen NC, Strandberg O, Vogel JW, Binette AP, . . ., Hansson O (2022) Biomarker-based prediction of longitudinal tau positron emission tomography in Alzheimer disease. JAMA Neurol 79(2): 149–158. https://doi.org/10.1001/jamaneurol.2021.4654

  • Mattsson N, Zetterberg H, Janelidze S, Insel PS, Andreasson U, Stomrud E, . . ., Investigators, A (2016) Plasma tau in Alzheimer disease. Neurology 87(17): 1827–1835. https://doi.org/10.1212/WNL.0000000000003246

  • Mayeux R (2004) Biomarkers: potential uses and limitations. NeuroRx 1(2):182–188. https://doi.org/10.1602/neurorx.1.2.182

    Article  Google Scholar 

  • Mayeux R, Schupf N (2011) Blood-based biomarkers for Alzheimer’s disease: plasma Abeta40 and Abeta42, and genetic variants. Neurobiol Aging 32(Suppl 1):S10-19. https://doi.org/10.1016/j.neurobiolaging.2011.09.004

    Article  CAS  Google Scholar 

  • McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, . . ., Phelps CH (2011) The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement 7(3): 263–269. https://doi.org/10.1016/j.jalz.2011.03.005

  • Mielke MM, Frank RD, Dage JL, Jeromin A, Ashton NJ, Blennow K, . . ., Petersen RC (2021) Comparison of plasma phosphorylated tau species with amyloid and tau positron emission tomography, neurodegeneration, vascular pathology, and cognitive outcomes. JAMA Neurol 78(9): 1108–1117. https://doi.org/10.1001/jamaneurol.2021.2293

  • Morgan AR, Touchard S, Leckey C, O'Hagan C, Nevado-Holgado AJ, Consortium, N, . . ., Alzheimer's, D (2019) Inflammatory biomarkers in Alzheimer's disease plasma. Alzheimers Dement 15(6): 776–787. https://doi.org/10.1016/j.jalz.2019.03.007

  • Mosconi L (2005) Brain glucose metabolism in the early and specific diagnosis of Alzheimer’s disease. FDG-PET studies in MCI and AD. Eur J Nucl Med Mol Imaging 32(4):486–510. https://doi.org/10.1007/s00259-005-1762-7

    Article  CAS  Google Scholar 

  • Nabers A, Perna L, Lange J, Mons U, Schartner J, Guldenhaupt J, . . ., Brenner H (2018) Amyloid blood biomarker detects Alzheimer's disease. EMBO Mol Med 10(5). https://doi.org/10.15252/emmm.201708763

  • Narayanan S, Shanker A, Khera T, Subramaniam B (2021) Neurofilament light: a narrative review on biomarker utility. Fac Rev 10:46. https://doi.org/10.12703/r/10-46

    Article  CAS  Google Scholar 

  • Olson BL, Holshouser BA, Britt W 3rd, Mueller C, Baqai W, Patra S, . . ., Kirsch WM (2008) Longitudinal metabolic and cognitive changes in mild cognitive impairment patients. Alzheimer Dis Assoc Disord 22(3): 269–277. https://doi.org/10.1097/WAD.0b013e3181750a65

  • Osborn KE, Khan OA, Kresge HA, Bown CW, Liu D, Moore EE, . . ., Jefferson AL (2019) Cerebrospinal fluid and plasma neurofilament light relate to abnormal cognition. Alzheimers Dement (Amst) 11: 700-709. https://doi.org/10.1016/j.dadm.2019.08.008

  • Ovod V, Ramsey KN, Mawuenyega KG, Bollinger JG, Hicks T, Schneider T, . . ., Bateman RJ (2017) Amyloid beta concentrations and stable isotope labeling kinetics of human plasma specific to central nervous system amyloidosis. Alzheimers Dement 13(8): 841–849. https://doi.org/10.1016/j.jalz.2017.06.2266

  • Palmqvist S, Insel PS, Stomrud E, Janelidze S, Zetterberg H, Brix B, . . ., Hansson O (2019) Cerebrospinal fluid and plasma biomarker trajectories with increasing amyloid deposition in Alzheimer's disease. EMBO Mol Med 11(12): e11170. https://doi.org/10.15252/emmm.201911170

  • Palmqvist S, Tideman P, Cullen N, Zetterberg H, Blennow K, Alzheimer's Disease Neuroimaging, I, . . . Hansson O (2021) Prediction of future Alzheimer's disease dementia using plasma phospho-tau combined with other accessible measures. Nat Med 27(6): 1034–1042. https://doi.org/10.1038/s41591-021-01348-z

  • Perez-Grijalba V, Romero J, Pesini P, Sarasa L, Monleon I, San-Jose I, . . ., Sarasa M (2019) Plasma Abeta42/40 ratio detects early stages of Alzheimer's disease and correlates with CSF and neuroimaging biomarkers in the AB255 Study. J Prev Alzheimers Dis 6(1): 34–41. https://doi.org/10.14283/jpad.2018.41

  • Pillai JA, Bena J, Bebek G, Bekris LM, Bonner-Jackson A, Kou L, . . ., Alzheimer's Disease Neuroimaging, I (2020) Inflammatory pathway analytes predicting rapid cognitive decline in MCI stage of Alzheimer's disease. Ann Clin Transl Neurol 7(7): 1225–1239. https://doi.org/10.1002/acn3.51109

  • Preische O, Schultz SA, Apel A, Kuhle J, Kaeser SA, Barro C, . . ., Dominantly Inherited Alzheimer, N (2019) Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease. Nat Med 25(2): 277–283. https://doi.org/10.1038/s41591-018-0304-3

  • Risacher SL, Saykin AJ (2013) Neuroimaging biomarkers of neurodegenerative diseases and dementia. Semin Neurol 33(4):386–416. https://doi.org/10.1055/s-0033-1359312

    Article  Google Scholar 

  • Seto M, Weiner RL, Dumitrescu L, Hohman TJ (2021) Protective genes and pathways in Alzheimer’s disease: moving towards precision interventions. Mol Neurodegener 16(1):29. https://doi.org/10.1186/s13024-021-00452-5

    Article  Google Scholar 

  • Sobow T, Flirski M, Kloszewska I, Liberski PP (2005) Plasma levels of alpha beta peptides are altered in amnestic mild cognitive impairment but not in sporadic Alzheimer's disease. Acta Neurobiol Exp (Wars) 65(2): 117–124. Retrieved from. https://www.ncbi.nlm.nih.gov/pubmed/15960295. Accessed 03/26/2022

  • Swanson CJ, Zhang Y, Dhadda S, Wang J, Kaplow J, Lai RYK, . . ., Cummings JL (2021) A randomized, double-blind, phase 2b proof-of-concept clinical trial in early Alzheimer's disease with lecanemab, an anti-Abeta protofibril antibody. Alzheimers Res Ther 13(1): 80. https://doi.org/10.1186/s13195-021-00813-8

  • Tapiola T, Alafuzoff I, Herukka SK, Parkkinen L, Hartikainen P, Soininen H, Pirttila T (2009) Cerebrospinal fluid {beta}-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain. Arch Neurol 66(3):382–389. https://doi.org/10.1001/archneurol.2008.596

    Article  Google Scholar 

  • Tarkowski E, Liljeroth AM, Minthon L, Tarkowski A, Wallin A, Blennow K (2003) Cerebral pattern of pro- and anti-inflammatory cytokines in dementias. Brain Res Bull 61(3):255–260. https://doi.org/10.1016/s0361-9230(03)00088-1

    Article  CAS  Google Scholar 

  • Tumati S, Herrmann N, Marotta G, Li A, Lanctot KL (2022) Blood-based biomarkers of agitation in Alzheimer’s disease: Advances and future prospects. Neurochem Int 152:105250. https://doi.org/10.1016/j.neuint.2021.105250

    Article  CAS  Google Scholar 

  • Umemneku Chikere CM, Wilson K, Graziadio S, Vale L, Allen AJ (2019) Diagnostic test evaluation methodology: A systematic review of methods employed to evaluate diagnostic tests in the absence of gold standard - an update. PLoS One 14(10):e0223832. https://doi.org/10.1371/journal.pone.0223832

    Article  CAS  Google Scholar 

  • West T, Kirmess KM, Meyer MR, Holubasch MS, Knapik SS, Hu Y, . . ., Yarasheski KE (2021) A blood-based diagnostic test incorporating plasma Abeta42/40 ratio, ApoE proteotype, and age accurately identifies brain amyloid status: findings from a multi cohort validity analysis. Mol Neurodegener 16(1): 30. https://doi.org/10.1186/s13024-021-00451-6

  • Zetterberg H, Burnham SC (2019) Blood-based molecular biomarkers for Alzheimer’s disease. Mol Brain 12(1):26. https://doi.org/10.1186/s13041-019-0448-1

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We acknowledge the support of staff at the Vanderbilt Center for Cognitive Medicine. Preparation of this review was partially supported by R01AG066159 and R56AG047992 (PN).

Funding

Preparation of this review was partially supported by R01AG066159 (Newhouse) and R56AG047992 (Newhouse).

Author information

Authors and Affiliations

  1. Vanderbilt University , 2301 Vanderbilt Place, Nashville, TN, 37235, USA

    Sanjana P. Padala & Paul A. Newhouse

  2. Center for Cognitive Medicine, Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN, USA

    Paul A. Newhouse

  3. VA-TVHS Geriatric Research Education and Clinical Center, Nashville, TN, USA

    Paul A. Newhouse

Authors
  1. Sanjana P. Padala
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Paul A. Newhouse
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Sanjana P. Padala: Conceptualization, literature search, synthesis, Writing—original draft.

Paul A. Newhouse: Supervision, helping with refining search, suggesting new papers, validation, Writing—review & editing.

Corresponding author

Correspondence to Sanjana P. Padala.

Ethics declarations

Ethics approval

Not applicable

Consent to participate

Not applicable

Consent for publication

Not applicable

Conflicts of interest/Competing interests

Both authors (Padala and Newhouse) have no conflicts of interest/competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Padala, S.P., Newhouse, P.A. Blood-based biomarkers in Alzheimer’s disease: a mini-review. Metab Brain Dis 38, 185–193 (2023). https://doi.org/10.1007/s11011-022-01114-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11011-022-01114-1

Keywords

Search

Navigation