Skip to main content

Clinical Meaningfulness of Biomarker Endpoints in Alzheimer’s Disease Research

  • Protocol
  • First Online:
Biomarkers for Preclinical Alzheimer’s Disease

Part of the book series: Neuromethods ((NM,volume 137))

Abstract

Advancement in biomarker research has enabled the in vivo detection of Alzheimer’s disease (AD) pathophysiology, including amyloid plaques, neurofibrillary tangles, and neuronal degeneration. AD biomarkers play an important role in characterizing the trajectory of AD and have been incorporated in the research criteria for AD diagnosis. The presence of abnormal biomarkers for AD pathology in cognitively normal individuals has further led to the proposal of a preclinical stage in the AD spectrum. With the emerging conceptual framework that intervention in the early stages of the disease offers the greatest chance of success in preventing or delaying AD progression, recent clinical trials are now focusing on individuals with preclinical AD. While there are clear benefits from the use of biomarkers in research settings such as the enrichment of clinical trial population to confirm the presence of target brain pathology and target engagement by the intervention, the role of biomarkers in the clinical setting is less clear, especially in asymptomatic individuals. Potential ethical issues also arise with the use of biomarkers due to the conflict between the principles of benefits and not doing harm. In fact, a unique set of ethical issues arises in asymptomatic individuals, such as the disclosure of genetic mutation status, and abnormal biomarker results when their diagnostic validity is uncertain. In this chapter, we will discuss the issues and clinical meaningfulness of biomarkers in AD research. Specifically, we will focus on the potential benefits and ethical considerations when genetics and biomarkers for amyloid, tau, and neurodegeneration are used in the early stages of AD.

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

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 119.00
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Serrano-Pozo A, Frosch MP, Masliah E, Hyman BT (2011) Neuropathological alterations in Alzheimer disease. Cold Spring Harb Perspect Med 1:a006189

    Article  PubMed  PubMed Central  Google Scholar 

  2. Jack CR, Knopman DS, Jagust WJ et al (2013) Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 12:207–216

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Dubois B, Feldman HH, Jacova C et al (2007) Research criteria for the diagnosis of Alzheimer’s disease: revising the NINCDS-ADRDA criteria. Lancet Neurol 6:734–746

    Article  PubMed  Google Scholar 

  4. McKhann GM, Knopman DS, Chertkow H et al (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 7:263–269

    Article  PubMed  PubMed Central  Google Scholar 

  5. Sperling RA, Aisen PS, Beckett LA et al (2011) Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the national institute on aging and the Alzheimer’s association workgroup. Alzheimers Dement 7:1–13

    Google Scholar 

  6. Dubois B, Feldman HH, Jacova C et al (2014) Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol 13:614–629

    Article  PubMed  Google Scholar 

  7. Dubois B, Hampel H, Feldman HH et al (2016) Preclinical Alzheimer’s disease: definition, natural history, and diagnostic criteria. Alzheimers Dement 12:292–323

    Article  PubMed  Google Scholar 

  8. Folch J, Petrov D, Ettcheto M et al (2016) Current research therapeutic strategies for Alzheimer’s disease treatment. Neural Plast 2016:1–15

    Article  Google Scholar 

  9. Bateman RJ, Benzinger TL, Berry S et al (2017) The DIAN-TU next generation Alzheimer’s prevention trial: adaptive design and disease progression model. Alzheimers Dement 13:8–19

    Article  PubMed  Google Scholar 

  10. Sperling RA, Aisen PS (2016) Anti-amyloid treatment of asymptomatic AD: A4 and beyond. Alzheimers Dement 12:P326–P327

    Article  Google Scholar 

  11. Goldman JS, Hahn SE, Williamson Catania J et al (2011) Genetic counseling and testing for Alzheimer disease: joint practice guidelines of the American college of medical genetics and the national society of genetic counselors. Genet Med 13:597–605

    Article  PubMed  PubMed Central  Google Scholar 

  12. Morris E, Chalkidou A, Hammers A et al (2016) Diagnostic accuracy of (18)F amyloid PET tracers for the diagnosis of Alzheimer’s disease: a systematic review and meta-analysis. Eur J Nucl Med Mol Imaging 43:374–385

    Article  CAS  PubMed  Google Scholar 

  13. Sevigny J, Chiao P, Bussière T et al (2016) The antibody aducanumab reduces Aβ plaques in Alzheimer’s disease. Nature 537:50–56

    Article  CAS  PubMed  Google Scholar 

  14. Gauthier S, Leuzy A, Racine E, Rosa-Neto P (2013) Diagnosis and management of Alzheimer’s disease: past, present and future ethical issues. Prog Neurobiol 110:102–113

    Article  CAS  PubMed  Google Scholar 

  15. Liu C, Kanekiyo T, Xu H, Bu G (2013) Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy. Nat Rev Neurol 9:106–118

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sperling RA, Aisen PS, Beckett LA et al (2011) Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the national institute on aging- Alzheimer’s association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7:280–292

    Article  PubMed  PubMed Central  Google Scholar 

  17. Steinbart EJ, S D MZ et al (2001) Impact of DNA testing for early-onset familial Alzheimer disease and frontotemporal dementia. Arch Neurol 58:1828

    Article  CAS  PubMed  Google Scholar 

  18. Bateman RJ, Xiong C, Benzinger TLS, Fagan AM, Goate A, Fox NC, Marcus DS, Cairns NJ, Xie X, Nlazey TM, Holtman DM, Santacruz A, Buckles V, Oliver A, Moulder K, Aisen PS, Ghetti B, Klunk WE, McDade E, Martins RN, Masters CL, Mayeux R, Ringman JM, Rossor MN, Schofield PR, Sperling RA, Salloway S, Morris JC (2013) Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. N Engl J Med 367:795–804.

    Google Scholar 

  19. Bateman RJ, Xiong C, Benzinger TLS et al (2012) Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. N Engl J Med 367:795–804

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Pepersack T (2008) Disclosing a diagnosis of Alzheimer’s disease. Rev Med Brux 29:89–93

    CAS  PubMed  Google Scholar 

  21. Nicole L Batsch, Mary S Mittelman (2012) World Alzheimer report 2012 overcoming the stigma of dementia. https://www.alz.org/documents_custom/world_report_2012_final.pdf. Accessed 8 Apr 2017

  22. Peters KR, Lynn Beattie B, Feldman HH (2013) A conceptual framework and ethics analysis for prevention trials of Alzheimer disease. Prog Neurobiol 110:114–123

    Article  PubMed  Google Scholar 

  23. Farrer LA, Cupples LA, Haines JL et al (1997) Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer disease meta analysis consortium. JAMA 278:1349–1356

    Article  CAS  PubMed  Google Scholar 

  24. Corder EH, Saunders AM, Strittmatter WJ et al (1993) Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 261:921–923

    Article  CAS  PubMed  Google Scholar 

  25. Kivipelto M, Rovio S, Ngandu T et al (2008) Apolipoprotein E ɛ4 magnifies lifestyle risks for dementia: a population-based study. J Cell Mol Med 12:2762–2771

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Peila R, Rodriguez BL, Launer LJ (2002) Type 2 diabetes, APOE gene, and the risk for dementia and related pathologies the Honolulu-Asia aging study. Diabetes 51:1256–1262

    Article  CAS  PubMed  Google Scholar 

  27. Ferrari C, W-L X, Wang H-X et al (2013) How can elderly apolipoprotein E ε4 carriers remain free from dementia? Neurobiol Aging 34:13–21

    Article  PubMed  Google Scholar 

  28. Green RC, Roberts JS, Cupples LA et al (2009) Disclosure of APOE genotype for risk of Alzheimer’s disease. N Engl J Med 361:245–254

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Strozyk D, Blennow K, White LR, Launer LJ (2003) CSF Abeta 42 levels correlate with amyloid-neuropathology in a population-based autopsy study. Neurology 60:652–656

    Article  CAS  PubMed  Google Scholar 

  30. Ikonomovic MD, Klunk WE, Abrahamson EE et al (2008) Post-mortem correlates of in vivo PiB-PET amyloid imaging in a typical case of Alzheimer’s disease. Brain 131:1630–1645

    Article  PubMed  PubMed Central  Google Scholar 

  31. Sojkova J, Driscoll I, Iacono D et al (2011) In vivo fibrillar β-amyloid detected using [11C]PiB positron emission tomography and neuropathologic assessment in older adults. Arch Neurol 68:232–240

    PubMed  PubMed Central  Google Scholar 

  32. Fagan AM, Xiong C, Jasielec MS et al (2014) Longitudinal change in CSF biomarkers in autosomal-dominant Alzheimer’s disease. Sci Transl Med 6:226ra30

    Article  PubMed  PubMed Central  Google Scholar 

  33. Leuzy A, Chiotis K, Hasselbalch SG et al (2016) Pittsburgh compound B imaging and cerebrospinal fluid amyloid-β in a multicentre European memory clinic study. Brain 139:2540–2553

    Article  PubMed  PubMed Central  Google Scholar 

  34. Chételat G, La Joie R, Villain N et al (2013) Amyloid imaging in cognitively normal individuals, at-risk populations and preclinical Alzheimer’s disease. Neuroimage Clin 2:356–365

    Article  PubMed  PubMed Central  Google Scholar 

  35. Price JL, Morris JC (1999) Tangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease. Ann Neurol 45:358–368

    Article  CAS  PubMed  Google Scholar 

  36. Albert MS, DeKosky ST, Dickson D et al (2011) The diagnosis of mild cognitive impairment 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 7:270–279

    Article  PubMed  PubMed Central  Google Scholar 

  37. Johnson KA, Minoshima S, Bohnen NI et al (2013) Appropriate use criteria for amyloid PET: a report of the amyloid imaging task force, the society of nuclear medicine and molecular imaging, and the Alzheimer’s association. Alzheimers Dement 9:E1–E16

    Article  Google Scholar 

  38. Okello A, Koivunen J, Edison P et al (2009) Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study. Neurology 73:754–760

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Salloway S, Sperling R, Fox NC et al (2014) Two phase 3 trials of Bapineuzumab in mild-to-moderate Alzheimer’s disease. N Engl J Med 370:322–333

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Hertze J, Minthon L, Zetterberg H et al (2010) Evaluation of CSF biomarkers as predictors of Alzheimer’s disease: a clinical follow-up study of 4.7 years. J Alzheimers Dis 21:1119–1128

    Article  CAS  PubMed  Google Scholar 

  41. Bertens D, Knol DL, Scheltens P, Visser PJ (2015) Temporal evolution of biomarkers and cognitive markers in the asymptomatic, MCI, and dementia stage of Alzheimer’s disease. Alzheimers Dement 11:511–522

    Article  PubMed  Google Scholar 

  42. Shulman MB, Harkins K, Green RC, Karlawish J (2013) Using AD biomarker research results for clinical care: a survey of ADNI investigators. Neurology 81:1114–1121

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Leuzy A, Zimmer ER, Heurling K et al (2014) Use of amyloid PET across the spectrum of Alzheimer’s disease: clinical utility and associated ethical issues. Amyloid 21:143–148

    Article  CAS  PubMed  Google Scholar 

  44. Laforce R, Rabinovici GD (2011) Amyloid imaging in the differential diagnosis of dementia: review and potential clinical applications. Alzheimers Res Ther 3:11

    Article  Google Scholar 

  45. Blennow K, Dubois B, Fagan AM et al (2015) Clinical utility of cerebrospinal fluid biomarkers in the diagnosis of early Alzheimer’s disease. Alzheimers Dement 11:58–69

    Article  PubMed  Google Scholar 

  46. Caselli R, Woodruff B (2016) Clinical impact of amyloid positron emission tomography—is it worth the cost? JAMA Neurol 73:1396–1398

    Article  PubMed  Google Scholar 

  47. Sabbagh MN, Cooper K, DeLange J et al (2010) Functional, global and cognitive decline correlates to accumulation of Alzheimer’s pathology in MCI and AD. Curr Alzheimer Res 7:280–286

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Nelson PT, Alafuzoff I, Bigio EH et al (2012) Correlation of Alzheimer disease neuropathologic changes with cognitive status: a review of the literature. J Neuropathol Exp Neurol 71:362–381

    Article  PubMed  PubMed Central  Google Scholar 

  49. Blennow K, Hampel H (2003) CSF markers for incipient Alzheimer’s disease. Lancet Neurol 2:605–613

    Article  CAS  PubMed  Google Scholar 

  50. Jack CR, Hampel HJ, Universities S et al (2016) A/T/N: an unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology 87:539–547

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Tapiola T, Alafuzoff I, Herukka S-K et al (2009) Cerebrospinal fluid β-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain. Arch Neurol 66:734–746

    Article  Google Scholar 

  52. Villemagne VL, Fodero-Tavoletti MT, Masters CL, Rowe CC (2015) Tau imaging: early progress and future directions. Lancet Neurol 14:114–124

    Article  PubMed  Google Scholar 

  53. Braak H, Braak E (1995) Staging of Alzheimer’s disease-related neurofibrillary changes. Neurobiol Aging 16:271–278. discussion 278–284

    Article  CAS  PubMed  Google Scholar 

  54. Johnson KA, Schultz A, Betensky RA et al (2016) Tau positron emission tomographic imaging in aging and early Alzheimer disease. Ann Neurol 79:110–119

    Article  PubMed  Google Scholar 

  55. Koopman K, Le Bastard N, Martin J, Nagels G (2009) Improved discrimination of autopsy-confirmed Alzheimer’s disease (AD) from non-AD dementias using CSF P-tau 181P. Neurochem Int 55:214–218

    Article  CAS  PubMed  Google Scholar 

  56. Maddalena A, Papassotiropoulos A (2003) Biochemical diagnosis of Alzheimer disease by measuring the cerebrospinal fluid ratio of phosphorylated tau protein to β-amyloid peptide42. Arch Neurol 60:1202–1206

    Article  PubMed  Google Scholar 

  57. Harada R, Okamura N, Furumoto S et al (2016) 18F-THK5351: a novel PET radiotracer for imaging neurofibrillary pathology in Alzheimer’s disease. J Nucl Med 57:208–214

    Article  CAS  PubMed  Google Scholar 

  58. Pontecorvo MJ, Devous MD Sr, Navitsky M et al (2017) Relationships between flortaucipir PET tau binding and amyloid burden, clinical diagnosis, age and cognition. Brain 140:748–763

    PubMed  PubMed Central  Google Scholar 

  59. Gauthier S, Feldman HH, Schneider LS et al (2016) Efficacy and safety of tau-aggregation inhibitor therapy in patients with mild or moderate Alzheimer’s disease: a randomised, controlled, double-blind, parallel-arm, phase 3 trial. Lancet 388:2873–2884

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Yanamandra K, Jiang H, Mahan TE et al (2015) Anti-tau antibody reduces insoluble tau and decreases brain atrophy. Ann Clin Transl Neurol 2:278–288

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Ng KP, Pascoal TA, Mathotaarachchi S et al (2017) Monoamine oxidase B inhibitor, selegiline, reduces 18 F-THK5351 uptake in the human brain. Alzheimers Res Ther 9:25

    Article  PubMed  PubMed Central  Google Scholar 

  62. Vermeiren C, Mercier J, Viot D et al (2015) T807, a reported selective tau tracer, binds with nanomolar affinity to monoamine oxidase a. Alzheimers Dement 11:P283

    Article  Google Scholar 

  63. Mosconi L (2013) Glucose metabolism in normal aging and Alzheimer’s disease: methodological and physiological considerations for PET studies. Clin Transl Imaging 1:217–233

    Article  Google Scholar 

  64. Ost M, Nylén K, Csajbok L et al (2006) Initial CSF total tau correlates with 1-year outcome in patients with traumatic brain injury. Neurology 67:1600–1604

    Article  CAS  PubMed  Google Scholar 

  65. Frisoni GB, Fox NC, Jack CR et al (2010) The clinical use of structural MRI in Alzheimer disease. Nat Rev Neurol 6:67–77

    Article  PubMed  PubMed Central  Google Scholar 

  66. Hansson O, Zetterberg H, Buchhave P et al (2006) Association between CSF biomarkers and incipient Alzheimer’s disease in patients with mild cognitive impairment: a follow-up study. Lancet Neurol 5:228–234

    Article  CAS  PubMed  Google Scholar 

  67. Skillbäck T, Farahmand BY, Rosén C et al (2015) Cerebrospinal fluid tau and amyloid-β 1-42 in patients with dementia. Brain 138:2716–2731

    Article  PubMed  Google Scholar 

  68. Mosconi L, Berti V, Glodzik L et al (2010) Pre-clinical detection of Alzheimer’s disease using FDG-PET, with or without amyloid imaging. J Alzheimers Dis 20:843–854

    Article  PubMed  PubMed Central  Google Scholar 

  69. Foster NL, Heidebrink JL, Clark CM et al (2007) FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer’s disease. Brain 130:2616–2635

    Article  PubMed  Google Scholar 

  70. Scheltens P, Leys D, Barkhof F et al (1992) Atrophy of medial temporal lobes on MRI in “probable” Alzheimer’s disease and normal ageing: diagnostic value and neuropsychological correlates. J Neurol Neurosurg Psychiatry 55:967–972

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Fotuhi M, Do D, Jack C (2012) Modifiable factors that alter the size of the hippocampus with ageing. Nat Rev Neurol 8:189–202

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

Kok Pin Ng is supported by the National Medical Research Council, Research Training Fellowship Grant (Singapore).

Pedro Rosa-Neto and Serge Gauthier are funded by the Canadian Institutes for Health Research.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Serge Gauthier .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Ng, K.P., Pascoal, T.A., Li, X., Rosa-Neto, P., Gauthier, S. (2018). Clinical Meaningfulness of Biomarker Endpoints in Alzheimer’s Disease Research. In: Perneczky, R. (eds) Biomarkers for Preclinical Alzheimer’s Disease. Neuromethods, vol 137. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7674-4_16

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-7674-4_16

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7673-7

  • Online ISBN: 978-1-4939-7674-4

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics