Skip to main content

Advertisement

Log in

Biomarker discovery for Alzheimer’s disease, frontotemporal lobar degeneration, and Parkinson’s disease

  • Review
  • Published:
Acta Neuropathologica Aims and scope Submit manuscript

Abstract

Ante-mortem diagnosis of neurodegenerative disorders based on clinical features alone is associated with variable sensitivity and specificity, and biomarkers can potentially improve the accuracy of clinical diagnosis. In patients suspected of having Alzheimer’s disease (AD), alterations in cerebrospinal fluid (CSF) biomarkers that reflect the neuropathologic changes of AD strongly support the diagnosis, although there is a trade-off between sensitivity and specificity due to similar changes in cognitively healthy subjects. Here, we review the current approaches in using CSF AD biomarkers (total tau, p-tau181, and Aβ42) to predict the presence of AD pathology, and our recent work using multi-analyte profiling to derive novel biomarkers for biofluid-based AD diagnosis. We also review our use of the multi-analyte profiling strategy to identify novel biomarkers that can distinguish between subtypes of frontotemporal lobar degeneration, and those at risk of developing cognitive impairment in Parkinson’s disease. Multi-analyte profiling is a powerful tool for biomarker discovery in complex neurodegenerative disorders, and analytes associated with one or more diseases may shed light on relevant biological pathways and potential targets for intervention.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Aarsland D, Andersen K, Larsen JP, Lolk A, Kragh-Sorensen P (2003) Prevalence and characteristics of dementia in Parkinson disease: an 8-year prospective study. Arch Neurol 60:387–392

    Article  PubMed  Google Scholar 

  2. Abdi F, Quinn JF, Jankovic J et al (2006) Detection of biomarkers with a multiplex quantitative proteomic platform in cerebrospinal fluid of patients with neurodegenerative disorders. J Alzheimers Dis 9:293–348

    PubMed  CAS  Google Scholar 

  3. Amonkar SD, Bertenshaw GP, Chen TH et al (2009) Development and preliminary evaluation of a multivariate index assay for ovarian cancer. PLoS One 4:e4599

    Article  PubMed  CAS  Google Scholar 

  4. Annunziato F, Cosmi L, Liotta F, Maggi E, Romagnani S (2009) Type 17 T helper cells-origins, features and possible roles in rheumatic disease. Nat Rev Rheumatol 5:325–331

    Article  PubMed  CAS  Google Scholar 

  5. The National Institute on Aging, Reagan Institute Working Group on Diagnostic Criteria for the Neuropathological Assessment of Alzheimer’s Disease (1997) Consensus recommendations for the postmortem diagnosis of Alzheimer’s disease. Neurobiol Aging 18:S1–S2

    Article  Google Scholar 

  6. APA (2010) DSM-5: the future of psychiatric diagnosis. APA

  7. Apostolova LG, Hwang KS, Andrawis JP et al (2010) 3D PIB and CSF biomarker associations with hippocampal atrophy in ADNI subjects. Neurobiol Aging 31(8):1284–1303

    Google Scholar 

  8. Bahl JM, Heegaard NH, Falkenhorst G et al (2009) The diagnostic efficiency of biomarkers in sporadic Creutzfeldt-Jakob disease compared to Alzheimer’s disease. Neurobiol Aging 30:1834–1841

    Article  PubMed  CAS  Google Scholar 

  9. Bergmann L (1965) The value of CSF-analysis in the diagnosis of MS. Acta Neurol Scand Suppl 13:559–561

    PubMed  Google Scholar 

  10. Bertenshaw GP, Yip P, Seshaiah P et al (2008) Multianalyte profiling of serum antigens and autoimmune and infectious disease molecules to identify biomarkers dysregulated in epithelial ovarian cancer. Cancer Epidemiol Biomarkers Prev 17:2872–2881

    Article  PubMed  CAS  Google Scholar 

  11. Bian H, Van Swieten JC, Leight S et al (2008) CSF biomarkers in frontotemporal lobar degeneration with known pathology. Neurology 70:1827–1835

    Article  PubMed  CAS  Google Scholar 

  12. Bibl M, Mollenhauer B, Esselmann H et al (2006) CSF amyloid-beta-peptides in Alzheimer’s disease, dementia with Lewy bodies and Parkinson’s disease dementia. Brain 129:1177–1187

    Article  PubMed  Google Scholar 

  13. Brookmeyer R, Johnson E, Ziegler-Graham K, Arrighi HM (2007) Forecasting the global burden of Alzheimer’s disease. Alzheimers Dement 3:186–191

    Article  PubMed  Google Scholar 

  14. Brown MP, Grundy WN, Lin D et al (2000) Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc Natl Acad Sci USA 97:262–267

    Article  PubMed  CAS  Google Scholar 

  15. Buerger K, Ewers M, Pirttila T et al (2006) CSF phosphorylated tau protein correlates with neocortical neurofibrillary pathology in Alzheimer’s disease. Brain 129:3035–3041

    Article  PubMed  Google Scholar 

  16. Buerger K, Frisoni G, Uspenskaya O et al (2009) Validation of Alzheimer’s disease CSF and plasma biological markers: the multicentre reliability study of the pilot European Alzheimer’s Disease Neuroimaging Initiative (E-ADNI). Exp Gerontol 44:579–585

    Article  PubMed  CAS  Google Scholar 

  17. Buter TC, van den Hout A, Matthews FE, Larsen JP, Brayne C, Aarsland D (2008) Dementia and survival in Parkinson disease: a 12-year population study. Neurology 70:1017–1022

    Article  PubMed  CAS  Google Scholar 

  18. Cairns NJ, Bigio EH, Mackenzie IR et al (2007) Neuropathologic diagnostic and nosologic criteria for frontotemporal lobar degeneration: consensus of the Consortium for Frontotemporal Lobar Degeneration. Acta Neuropathol 114:5–22

    Article  PubMed  Google Scholar 

  19. Castano EM, Roher AE, Esh CL, Kokjohn TA, Beach T (2006) Comparative proteomics of cerebrospinal fluid in neuropathologically-confirmed Alzheimer’s disease and non-demented elderly subjects. Neurol Res 28:155–163

    Article  PubMed  CAS  Google Scholar 

  20. Chen-Plotkin AS, Geser F, Plotkin JB et al (2008) Variations in the progranulin gene affect global gene expression in frontotemporal lobar degeneration. Hum Mol Genet 17:1349–1362

    Article  PubMed  CAS  Google Scholar 

  21. Clark CM, Xie S, Chittams J et al (2003) Cerebrospinal fluid tau and beta-amyloid: how well do these biomarkers reflect autopsy-confirmed dementia diagnoses? Arch Neurol 60:1696–1702

    Article  PubMed  Google Scholar 

  22. Clifford DB, Fagan AM, Holtzman DM et al (2009) CSF biomarkers of Alzheimer disease in HIV-associated neurologic disease. Neurology 73:1982–1987

    Article  PubMed  CAS  Google Scholar 

  23. Compta Y, Marti MJ, Ibarretxe-Bilbao N et al (2009) Cerebrospinal tau, phospho-tau, and beta-amyloid and neuropsychological functions in Parkinson’s disease. Mov Disord 24:2203–2210

    Article  PubMed  Google Scholar 

  24. Delaleu N, Immervoll H, Cornelius J, Jonsson R (2008) Biomarker profiles in serum and saliva of experimental Sjogren’s syndrome: associations with specific autoimmune manifestations. Arthritis Res Ther 10:R22

    Article  PubMed  CAS  Google Scholar 

  25. Ellis KA, Bush AI, Darby D et al (2009) The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging: methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer’s disease. Int Psychogeriatr 21:672–687

    Article  PubMed  Google Scholar 

  26. Engelborghs S, Sleegers K, Cras P et al (2007) No association of CSF biomarkers with APOEepsilon4, plaque and tangle burden in definite Alzheimer’s disease. Brain 130:2320–2326

    Article  PubMed  Google Scholar 

  27. Fagan AM, Mintun MA, Shah AR et al (2009) Cerebrospinal fluid tau and ptau(181) increase with cortical amyloid deposition in cognitively normal individuals: implications for future clinical trials of Alzheimer’s disease. EMBO Mol Med 1:371–380

    Article  PubMed  CAS  Google Scholar 

  28. Fagan AM, Roe CM, Xiong C, Mintun MA, Morris JC, Holtzman DM (2007) Cerebrospinal fluid tau/beta-amyloid(42) ratio as a prediction of cognitive decline in nondemented older adults. Arch Neurol 64:343–349

    Article  PubMed  Google Scholar 

  29. Finehout EJ, Franck Z, Choe LH, Relkin N, Lee KH (2007) Cerebrospinal fluid proteomic biomarkers for Alzheimer’s disease. Ann Neurol 61:120–129

    Article  PubMed  CAS  Google Scholar 

  30. Fleisher AS, Raman R, Siemers ER et al (2008) Phase 2 safety trial targeting amyloid beta production with a gamma-secretase inhibitor in Alzheimer disease. Arch Neurol 65:1031–1038

    Article  PubMed  Google Scholar 

  31. Forman MS, Farmer J, Johnson JK et al (2006) Frontotemporal dementia: clinicopathological correlations. Ann Neurol 59:952–962

    Article  PubMed  Google Scholar 

  32. Foulds P, McAuley E, Gibbons L et al (2008) TDP-43 protein in plasma may index TDP-43 brain pathology in Alzheimer’s disease and frontotemporal lobar degeneration. Acta Neuropathol 116:141–146

    Article  PubMed  CAS  Google Scholar 

  33. Fujishiro H, Ferman TJ, Boeve BF et al (2008) Validation of the neuropathologic criteria of the third consortium for dementia with Lewy bodies for prospectively diagnosed cases. J Neuropathol Exp Neurol 67:649–656

    Article  PubMed  Google Scholar 

  34. Gisslen M, Krut J, Andreasson U et al (2009) Amyloid and tau cerebrospinal fluid biomarkers in HIV infection. BMC Neurol 9:63

    Article  PubMed  CAS  Google Scholar 

  35. Golub TR, Slonim DK, Tamayo P et al (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286:531–537

    Article  PubMed  CAS  Google Scholar 

  36. Gray H (1912) History of lumbar puncture (rachicentesis). Arch Neurol Psychiatry 6:61–69

    Google Scholar 

  37. Grossman M, Farmer J, Leight S et al (2005) Cerebrospinal fluid profile in frontotemporal dementia and Alzheimer’s disease. Ann Neurol 57:721–729

    Article  PubMed  Google Scholar 

  38. Gurbel PA, Kreutz RP, Bliden KP, DiChiara J, Tantry US (2008) Biomarker analysis by fluorokine multianalyte profiling distinguishes patients requiring intervention from patients with long-term quiescent coronary artery disease: a potential approach to identify atherosclerotic disease progression. Am Heart J 155:56–61

    Article  PubMed  CAS  Google Scholar 

  39. Gustafson DR, Skoog I, Rosengren L, Zetterberg H, Blennow K (2007) Cerebrospinal fluid beta-amyloid 1–42 concentration may predict cognitive decline in older women. J Neurol Neurosurg Psychiatry 78:461–464

    Article  PubMed  Google Scholar 

  40. Hely MA, Reid WG, Adena MA, Halliday GM, Morris JG (2008) The Sydney multicenter study of Parkinson’s disease: the inevitability of dementia at 20 years. Mov Disord 23:837–844

    Article  PubMed  Google Scholar 

  41. Hodges JR, Davies RR, Xuereb JH et al (2004) Clinicopathological correlates in frontotemporal dementia. Ann Neurol 56:399–406

    Article  PubMed  Google Scholar 

  42. Hu WT, Chen-Plotkin A, Arnold SE et al (2010) Novel CSF biomarkers for Alzheimer’s disease and mild cognitive impairment. Acta Neuropathol 119:669–678

    Article  PubMed  CAS  Google Scholar 

  43. Hu WT, Chen-Plotkin A, Grossman M et al (2010) Novel CSF biomarkers for frontotemporal lobar degenerations. Neurology (in press)

  44. Hu WT, Mandrekar JN, Parisi JE et al (2007) Clinical features of pathologic subtypes of behavioral-variant frontotemporal dementia. Arch Neurol 64:1611–1616

    Article  PubMed  Google Scholar 

  45. Hu WT, McMillan C, Libon DJ et al (2010) Multi-modal predictors for Alzheimer’s disease in non-fluent primary progressive aphasia. Neurology (in press)

  46. Hu WT, Seelaar H, Josephs KA et al (2009) Survival profiles of patients with frontotemporal dementia and motor neuron disease. Arch Neurol 66:1359–1364

    Article  PubMed  Google Scholar 

  47. Innogenetics. INNO-BIA AlzBio3

  48. Jack CR Jr, Knopman DS, Jagust WJ et al (2010) Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol 9:119–128

    Article  PubMed  CAS  Google Scholar 

  49. Kasuga K, Tokutake T, Ishikawa A et al (2010) Differential levels of alpha-synuclein, beta-amyloid42, tau in CSF between patients with dementia with Lewy bodies, Alzheimer’s disease. J Neurol Neurosurg Psychiatry 81:608–610

    Article  PubMed  Google Scholar 

  50. Koster MP, Pennings JL, Imholz S et al (2009) Bead-based multiplexed immunoassays to identify new biomarkers in maternal serum to improve first trimester Down syndrome screening. Prenat Diagn 29:857–862

    Article  PubMed  CAS  Google Scholar 

  51. Ladogana A, Sanchez-Juan P, Mitrova E et al (2009) Cerebrospinal fluid biomarkers in human genetic transmissible spongiform encephalopathies. J Neurol 256:1620–1628

    Article  PubMed  CAS  Google Scholar 

  52. Lewczuk P, Beck G, Ganslandt O et al (2006) International quality control survey of neurochemical dementia diagnostics. Neurosci Lett 409:1–4

    Article  PubMed  CAS  Google Scholar 

  53. Lippa CF, Duda JE, Grossman M et al (2007) DLB and PDD boundary issues: diagnosis, treatment, molecular pathology, and biomarkers. Neurology 68:812–819

    Article  PubMed  CAS  Google Scholar 

  54. Lui JK, Laws SM, Li QX et al (2010) Plasma amyloid-beta as a biomarker in Alzheimer’s disease: the AIBL Study of Aging. J Alzheimers Dis 20(4):1233–1242

    Google Scholar 

  55. Mattsson N, Zetterberg H, Hansson O et al (2009) CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment. JAMA 302:385–393

    Article  PubMed  CAS  Google Scholar 

  56. Miller DJ, Wang Y, Kesidis G (2008) Emergent unsupervised clustering paradigms with potential application to bioinformatics. Front Biosci 13:677–690

    Article  PubMed  CAS  Google Scholar 

  57. Mollenhauer B, Cullen V, Kahn I et al (2008) Direct quantification of CSF alpha-synuclein by ELISA and first cross-sectional study in patients with neurodegeneration. Exp Neurol 213:315–325

    Article  PubMed  CAS  Google Scholar 

  58. Morris JC, Roe CM, Xiong C et al (2010) APOE predicts amyloid-beta but not tau Alzheimer pathology in cognitively normal aging. Ann Neurol 67:122–131

    Article  PubMed  CAS  Google Scholar 

  59. Nettiksimmons J, Harvey D, Brewer J et al (2010) Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline. Neurobiol Aging 31(8):1419–1428

    Google Scholar 

  60. Neumann M, Kwong LK, Lee EB et al (2009) Phosphorylation of S409/410 of TDP-43 is a consistent feature in all sporadic and familial forms of TDP-43 proteinopathies. Acta Neuropathol 117:137–149

    Article  PubMed  CAS  Google Scholar 

  61. Ohrfelt A, Grognet P, Andreasen N et al (2009) Cerebrospinal fluid alpha-synuclein in neurodegenerative disorders-a marker of synapse loss? Neurosci Lett 450:332–335

    Article  PubMed  CAS  Google Scholar 

  62. Pang H, Zhao H (2008) Building pathway clusters from Random Forests classification using class votes. BMC Bioinform 9:87

    Article  CAS  Google Scholar 

  63. Pennings JL, Koster MP, Rodenburg W, Schielen PC, de Vries A (2009) Discovery of novel serum biomarkers for prenatal Down syndrome screening by integrative data mining. PLoS One 4:e8010

    Article  PubMed  CAS  Google Scholar 

  64. Portelius E, Dean RA, Gustavsson MK et al (2010) A novel Abeta isoform pattern in CSF reflects gamma-secretase inhibition in Alzheimer disease. Alzheimers Res Ther 2:7

    Article  PubMed  CAS  Google Scholar 

  65. Ray S, Britschgi M, Herbert C et al (2007) Classification and prediction of clinical Alzheimer’s diagnosis based on plasma signaling proteins. Nat Med 13:1359–1362

    Article  PubMed  CAS  Google Scholar 

  66. Reijn TS, Rikkert MO, van Geel WJ, de Jong D, Verbeek MM (2007) Diagnostic accuracy of ELISA and xMAP technology for analysis of amyloid beta(42) and tau proteins. Clin Chem 53:859–865

    Article  PubMed  CAS  Google Scholar 

  67. Saeys Y, Inza I, Larranaga P (2007) A review of feature selection techniques in bioinformatics. Bioinformatics 23:2507–2517

    Article  PubMed  CAS  Google Scholar 

  68. Shaw LM, Korecka M, Clark CM, Lee VM, Trojanowski JQ (2007) Biomarkers of neurodegeneration for diagnosis and monitoring therapeutics. Nat Rev Drug Discov 6:295–303

    Article  PubMed  CAS  Google Scholar 

  69. Shaw LM, Vanderstichele H, Knapik-Czajka M et al (2009) Cerebrospinal fluid biomarker signature in Alzheimer’s disease neuroimaging initiative subjects. Ann Neurol 65:403–413

    Article  PubMed  CAS  Google Scholar 

  70. Siderowf A, Xie SX, Hurtig H et al (2010) CSF amyloid beta 1-42 predicts cognitive decline in Parkinson’s disease. Ann Neurol (in press)

  71. Steinacker P, Hendrich C, Sperfeld AD et al (2008) TDP-43 in cerebrospinal fluid of patients with frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Arch Neurol 65:1481–1487

    Article  PubMed  Google Scholar 

  72. Steinacker P, Mollenhauer B, Bibl M et al (2004) Heart fatty acid binding protein as a potential diagnostic marker for neurodegenerative diseases. Neurosci Lett 370:36–39

    Article  PubMed  CAS  Google Scholar 

  73. Stern Y, Marder K, Tang MX, Mayeux R (1993) Antecedent clinical features associated with dementia in Parkinson’s disease. Neurology 43:1690–1692

    PubMed  CAS  Google Scholar 

  74. Stomrud E, Hansson O, Blennow K, Minthon L, Londos E (2007) Cerebrospinal fluid biomarkers predict decline in subjective cognitive function over 3 years in healthy elderly. Dement Geriatr Cogn Disord 24:118–124

    Article  PubMed  CAS  Google Scholar 

  75. Tibshirani R, Hastie T, Narasimhan B, Chu G (2002) Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc Natl Acad Sci USA 99:6567–6572

    Article  PubMed  CAS  Google Scholar 

  76. Trojanowski JQ, Vandeerstichele H, Korecka M et al (2010) Update on the biomarker core of the Alzheimer’s Disease Neuroimaging Initiative subjects. Alzheimers Dement 6:230–238

    Article  PubMed  CAS  Google Scholar 

  77. Uc EY, McDermott MP, Marder KS et al (2009) Incidence of and risk factors for cognitive impairment in an early Parkinson disease clinical trial cohort. Neurology 73:1469–1477

    Article  PubMed  CAS  Google Scholar 

  78. van Eersel J, Bi M, Ke YD et al (2009) Phosphorylation of soluble tau differs in Pick’s disease and Alzheimer’s disease brains. J Neural Transm 116:1243–1251

    Article  PubMed  CAS  Google Scholar 

  79. Verwey NA, van der Flier WM, Blennow K et al (2009) A worldwide multicentre comparison of assays for cerebrospinal fluid biomarkers in Alzheimer’s disease. Ann Clin Biochem 46:235–240

    Article  PubMed  CAS  Google Scholar 

  80. Walhovd KB, Fjell AM, Brewer J et al (2010) Combining MR imaging, positron-emission tomography, and CSF biomarkers in the diagnosis and prognosis of Alzheimer disease. Am J Neuroradiol 31:347–354

    Google Scholar 

  81. Zhang H, Yu CY, Singer B (2003) Cell and tumor classification using gene expression data: construction of forests. Proc Natl Acad Sci USA 100:4168–4172

    Article  PubMed  CAS  Google Scholar 

  82. Zhang J, Sokal I, Peskind ER et al (2008) CSF multianalyte profile distinguishes Alzheimer and Parkinson diseases. Am J Clin Pathol 129:526–529

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to John Q. Trojanowski.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hu, W.T., Chen-Plotkin, A., Arnold, S.E. et al. Biomarker discovery for Alzheimer’s disease, frontotemporal lobar degeneration, and Parkinson’s disease. Acta Neuropathol 120, 385–399 (2010). https://doi.org/10.1007/s00401-010-0723-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00401-010-0723-9

Keywords

Navigation