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Current Role for Biomarkers in Clinical Diagnosis of Alzheimer Disease and Frontotemporal Dementia

  • Nasim Sheikh-Bahaei
  • Seyed Ahmad Sajjadi
  • Aimee L. PierceEmail author
Dementia (J Pillai, Section Editor)
Part of the following topical collections:
  1. Topical Collection on Dementia

Abstract

Purpose of review Alzheimer’s disease (AD) and frontotemporal dementia can often be diagnosed accurately with careful clinical history, cognitive testing, neurological examination, and structural brain MRI. However, there are certain circumstances wherein detection of specific biomarkers of neurodegeneration or underlying AD pathology will impact the clinical diagnosis or treatment plan. We will review the currently available biomarkers for AD and frontotemporal dementia (FTD) and discuss their clinical importance.

Recent findings With the advent of 18F-labeled tracers that bind amyloid plaques, amyloid PET is now clinically available for the detection of amyloid pathology and to aid in a biomarker-supported diagnosis of AD or mild cognitive impairment (MCI) due to AD. It is not yet possible to test for the specific FTD pathologies (tau or TDP-43); however, a diagnosis of FTD may be “imaging supported” based upon specific MRI or FDG-PET findings. Cerebrospinal fluid measures of amyloid-beta, total-tau, and phospho-tau are clinically available and allow detection of both of the cardinal pathologies of AD: amyloid and tau pathology.

Summary It is appropriate to pursue biomarker testing in cases of MCI and dementia when there remains diagnostic uncertainty and the result will impact diagnosis or treatment. Practically speaking, due to the rising prevalence of amyloid positivity with advancing age, measurement of biomarkers in cases of MCI and dementia is most helpful in early-onset patients, patients with atypical clinical presentations, or when considering referral for AD clinical trials.

Keywords

Alzheimer’s disease Frontotemporal dementia Frontotemporal lobar degeneration Imaging biomarkers Clinical diagnosis 

Notes

Compliance with Ethical Standards

Conflict of Interest

N.S.-B. and S.A.S. each declare no potential conflicts of interest.

A.L.P. reports contracts from Avid Radiopharmaceuticals, Eli Lilly, Transition Therapeutics (previously Elan), Stemedica, Biogen, Janssen, Axovant, and Roche/Genentech, as well as personal fees from Lundbeck, outside the submitted work.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

References and Recommended Reading

Papers of particular interest, published recently, have been highlighted as: • Of importance

  1. 1.
    Beach TG, Monsell SE, Phillips LE, Kukull W. Accuracy of the clinical diagnosis of Alzheimer disease at National Institute on Aging Alzheimer disease centers, 2005–2010. J Neuropathol Exp Neurol. 2012;71(4):266–73.CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Balasa M, Gelpi E, Martin I, Antonell A, Rey MJ, Grau-Rivera O, et al. Diagnostic accuracy of behavioral variant frontotemporal dementia consortium criteria (FTDC) in a clinicopathological cohort. Neuropathol Appl Neurobiol. 2015;41(7):882–92.CrossRefPubMedGoogle Scholar
  3. 3.
    • Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Cedarbaum J, et al. 2014 update of the Alzheimer’s disease neuroimaging initiative: a review of papers published since its inception. Alzheimers Dement. 2015;11(6):e1–120. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is one of the most important studies of longitudinal changes in cognition and biomarkers in healthy elderly, MCI, and AD patients in the USA, and has developed numerous standard imaging protocols and analytics for the field. Several studies worldwide have been partially modeled on ADNI, in Europe, Japan, and AustraliaCrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Bateman RJ, Xiong C, Benzinger TL, Fagan AM, Goate A, Fox NC, et al. Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. N Engl J Med. 2012;367(9):795–804.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    McKhann GM, Knopman DS. 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. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2011;7(3):263–9.CrossRefGoogle Scholar
  6. 6.
    Neary D, Snowden JS, Gustafson L, Passant U, Stuss D, Black S, et al. Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology. 1998;51(6):1546–54.CrossRefPubMedGoogle Scholar
  7. 7.
    Diehl-Schmid J, Grimmer T, Drzezga A, Bornschein S, Perneczky R, Forstl H, et al. Longitudinal changes of cerebral glucose metabolism in semantic dementia. Dement Geriatr Cogn Disord. 2006;22(4):346–51.CrossRefPubMedGoogle Scholar
  8. 8.
    Bang J, Spina S, Miller BL. Frontotemporal dementia. Lancet. 2015;386(10004):1672–82.CrossRefPubMedGoogle Scholar
  9. 9.
    Rascovsky K, Hodges JR, Knopman D, Mendez MF, Kramer JH, Neuhaus J, et al. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain. 2011;134(Pt 9):2456–77.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Mesulam M. Primary progressive aphasia—a language-based dementia. N Engl J Med. 2003;349(16):1535–42.CrossRefPubMedGoogle Scholar
  11. 11.
    Kertesz A, McMonagle P, Blair M, Davidson W, Munoz DG. The evolution and pathology of frontotemporal dementia. Brain. 2005;128(Pt 9):1996–2005.CrossRefPubMedGoogle Scholar
  12. 12.
    Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, et al. Classification of primary progressive aphasia and its variants. Neurology. 2011;76(11):1006–14.CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Sajjadi SA, Sheikh-Bahaei N, Cross J, Gillard JH, Scoffings D, Nestor PJ. Can MRI visual assessment differentiate the variants of primary-progressive aphasia? AJNR Am J Neuroradiol. 2017;38(5):954–60.CrossRefPubMedGoogle Scholar
  14. 14.
    Cairns NJ, Bigio EH, Mackenzie IR, Neumann M, Lee VM, Hatanpaa KJ, et al. Neuropathologic diagnostic and nosologic criteria for frontotemporal lobar degeneration: consensus of the consortium for frontotemporal lobar degeneration. Acta Neuropathol. 2007;114(1):5–22.CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Neumann M, Rademakers R, Roeber S, Baker M, Kretzschmar HA, Mackenzie IR. A new subtype of frontotemporal lobar degeneration with FUS pathology. Brain. 2009;132(Pt 11):2922–31.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    NICE. Dementia: supporting people with dementia and their carers in health and social care | Guidance and guidelines |National Institute for Health and Care Excellence. 2016.Google Scholar
  17. 17.
    Soucy JP, Bartha R, Bocti C, Borrie M, Burhan AM, Laforce R, et al. Clinical applications of neuroimaging in patients with Alzheimer’s disease: a review from the fourth Canadian consensus conference on the diagnosis and treatment of dementia 2012. Alzheimers Res Ther. 2013;5(Suppl 1):S3.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Filippi M, Agosta F, Barkhof F, Dubois B, Fox NC, Frisoni GB, et al. EFNS task force: the use of neuroimaging in the diagnosis of dementia. Eur J Neurol. 2012;19(12):e131–40. 1487-501CrossRefPubMedGoogle Scholar
  19. 19.
    Ossenkoppele R, Cohn-Sheehy BI, La Joie R, Vogel JW, Moller C, Lehmann M, et al. Atrophy patterns in early clinical stages across distinct phenotypes of Alzheimer’s disease. Hum Brain Mapp 2015;36(11):4421–4437.Google Scholar
  20. 20.
    Pan PL, Song W, Yang J, Huang R, Chen K, Gong QY, et al. Gray matter atrophy in behavioral variant frontotemporal dementia: a meta-analysis of voxel-based morphometry studies. Dement Geriatr Cogn Disord. 2012;33(2–3):141–8.CrossRefPubMedGoogle Scholar
  21. 21.
    Rohrer JD, Warren JD, Modat M, Ridgway GR, Douiri A, Rossor MN, et al. Patterns of cortical thinning in the language variants of frontotemporal lobar degeneration. Neurology. 2009;72(18):1562–9.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Gorno-Tempini ML, Dronkers NF, Rankin KP, Ogar JM, Phengrasamy L, Rosen HJ, et al. Cognition and anatomy in three variants of primary progressive aphasia. Ann Neurol. 2004;55(3):335–46.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Scheltens P, Leys D, Barkhof F. Atrophy of medial temporal lobes on MRI in “probable” Alzheimer’s disease and normal ageing: diagnostic value and neuropsychological correlates. J Neurol. 1992;8:967–72.Google Scholar
  24. 24.
    Pasquier F, Leys D, Weerts JG, Mounier-Vehier F, Barkhof F, Scheltens P. Inter- and intraobserver reproducibility of cerebral atrophy assessment on MRI scans with hemispheric infarcts. Eur Neurol. 1996;36(5):268–72.CrossRefPubMedGoogle Scholar
  25. 25.
    • Harper L, Barkhof F, Fox NC, Schott JM. Using visual rating to diagnose dementia: a critical evaluation of MRI atrophy scales. J Neurol Neurosurg Psychiatry. 2015;86(11):1225–33. In this systemic review, different cerebral atrophy rating scales for dementia have been examined to highlight the diagnostic potential of these clinically applicable toolsCrossRefPubMedGoogle Scholar
  26. 26.
    Wahlund LO, Barkhof F, Fazekas F, Bronge L, Augustin M, Sjogren M, et al. A new rating scale for age-related white matter changes applicable to MRI and CT. Stroke. 2001;32(6):1318–22.CrossRefPubMedGoogle Scholar
  27. 27.
    Wahlund LO, Westman E, van Westen D, Wallin A, Shams S, Cavallin L, et al. Imaging biomarkers of dementia: recommended visual rating scales with teaching cases. Insights Imaging 2017;8(1):79–90.Google Scholar
  28. 28.
    O'Brien JT, Firbank MJ, Davison C, Barnett N, Bamford C, Donaldson C, et al. 18F-FDG PET and perfusion SPECT in the diagnosis of Alzheimer and Lewy body dementias. J Nucl Med. 2014;55(12):1959–65.CrossRefPubMedGoogle Scholar
  29. 29.•
    Smailagic N, Vacante M, Hyde C, Martin S, Ukoumunne O, Sachpekidis C. (1)(8)F-FDG PET for the early diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane database Syst rev. 2015;1:Cd010632. In this Cochrane systemic review, authors searched all the major databases and included and analyzed all the studies that evaluated the diagnostic accuracy of FDG PET to detemine the conversion from MCI to AD or other forms of dementia.Google Scholar
  30. 30.
    Foster NL, Heidebrink JL, Clark CM, Jagust WJ, Arnold SE, Barbas NR, et al. FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer’s disease. Brain. 2007;130(Pt 10):2616–35.CrossRefPubMedGoogle Scholar
  31. 31.
    Lim SM, Katsifis A, Villemagne VL, Best R, Jones G, Saling M, et al. The 18F-FDG PET cingulate island sign and comparison to 123I-beta-CIT SPECT for diagnosis of dementia with Lewy bodies. J Nucl Med. 2009;50(10):1638–45.CrossRefPubMedGoogle Scholar
  32. 32.
    Kono AK, Ishii K, Sofue K, Miyamoto N, Sakamoto S, Mori E. Fully automatic differential diagnosis system for dementia with Lewy bodies and Alzheimer’s disease using FDG-PET and 3D-SSP. Eur J Nucl Med Mol Imaging. 2007;34(9):1490–7.CrossRefPubMedGoogle Scholar
  33. 33.
    Arlt S, Brassen S, Jahn H, Wilke F, Eichenlaub M, Apostolova I, et al. Association between FDG uptake, CSF biomarkers and cognitive performance in patients with probable Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2009;36(7):1090–100.CrossRefPubMedGoogle Scholar
  34. 34.
    Jack CR Jr, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12(2):207–16.CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Drzezga A, Lautenschlager N, Siebner H, Riemenschneider M, Willoch F, Minoshima S, et al. Cerebral metabolic changes accompanying conversion of mild cognitive impairment into Alzheimer’s disease: a PET follow-up study. Eur J Nucl Med Mol Imaging. 2003;30(8):1104–13.CrossRefPubMedGoogle Scholar
  36. 36.
    Silverman DH, Small GW, Phelps ME. Clinical value of neuroimaging in the diagnosis of dementia. Sensitivity and specificity of regional cerebral metabolic and other parameters for early identification of Alzheimer’s disease. Clin Positron Imaging. 1999;2(3):119–30.CrossRefPubMedGoogle Scholar
  37. 37.
    Mosconi L. 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. 2005;32(4):486–510.CrossRefPubMedGoogle Scholar
  38. 38.
    Lehmann M, Ghosh PM, Madison C, Laforce R Jr, Corbetta-Rastelli C, Weiner MW, et al. Diverging patterns of amyloid deposition and hypometabolism in clinical variants of probable Alzheimer’s disease. Brain. 2013;136(Pt 3):844–58.CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Verfaillie SC, Adriaanse SM, Binnewijzend MA, Benedictus MR, Ossenkoppele R, Wattjes MP, et al. Cerebral perfusion and glucose metabolism in Alzheimer’s disease and frontotemporal dementia: two sides of the same coin? Eur Radiol. 2015;25(10):3050–9.CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Diehl-Schmid J, Grimmer T, Drzezga A, Bornschein S, Riemenschneider M, Forstl H, et al. Decline of cerebral glucose metabolism in frontotemporal dementia: a longitudinal 18F-FDG-PET-study. Neurobiol Aging. 2007;28(1):42–50.CrossRefPubMedGoogle Scholar
  41. 41.
    Rabinovici GD, Jagust WJ, Furst AJ, Ogar JM, Racine CA, Mormino EC, et al. Abeta amyloid and glucose metabolism in three variants of primary progressive aphasia. Ann Neurol. 2008;64(4):388–401.CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Ng S, Villemagne VL, Berlangieri S, Lee ST, Cherk M, Gong SJ, et al. Visual assessment versus quantitative assessment of 11C-PIB PET and 18F-FDG PET for detection of Alzheimer’s disease. J Nucl Med. 2007;48(4):547–52.CrossRefPubMedGoogle Scholar
  43. 43.
    Womack KB, Diaz-Arrastia R, Aizenstein HJ, Arnold SE, Barbas NR, Boeve BF, et al. Temporoparietal hypometabolism in frontotemporal lobar degeneration and associated imaging diagnostic errors. Arch Neurol. 2011;68(3):329–37.CrossRefPubMedGoogle Scholar
  44. 44.
    Rabinovici GD, Rosen HJ, Alkalay A, Kornak J, Furst AJ, Agarwal N, et al. Amyloid vs FDG-PET in the differential diagnosis of AD and FTLD. Neurology. 2011;77(23):2034–42.CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Herholz K. The role of PET quantification in neurological imaging: FDG and amyloid imaging in dementia. Clinical and Translational Imaging. 2014;2(4):321–30.CrossRefGoogle Scholar
  46. 46.
    Vandenberghe R, Van Laere K, Ivanoiu A, Salmon E, Bastin C, Triau E, et al. 18F-Flutemetamol amyloid imaging in Alzheimer disease and mild cognitive impairment: a phase 2 trial. Ann Neurol 2010;68(3):319–329.Google Scholar
  47. 47.
    Wong DF, Rosenberg PB, Zhou Y, Kumar A, Raymont V, Ravert HT, et al. In vivo imaging of amyloid deposition in Alzheimer disease using the radioligand 18F-AV-45 (florbetapir [corrected] F 18). Journal of nuclear medicine : official publication, Society of Nuclear Medicine. 2010;51(6):913–20.CrossRefGoogle Scholar
  48. 48.
    Rowe CC, Ackerman U, Browne W, Mulligan R, Pike KL, O'Keefe G, et al. Imaging of amyloid beta in Alzheimer’s disease with 18F-BAY94-9172, a novel PET tracer: proof of mechanism. Lancet Neurol. 2008;7(2):129–35.CrossRefPubMedGoogle Scholar
  49. 49.
    Wolk DA, Zhang Z, Boudhar S, Clark CM, Pontecorvo MJ, Arnold SE. Amyloid imaging in Alzheimer’s disease: comparison of florbetapir and Pittsburgh compound-B positron emission tomography. J Neurol Neurosurg Psychiatry. 2012;83(9):923–6.CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Landau SM, Thomas BA, Thurfjell L, Schmidt M, Margolin R, Mintun M, et al. Amyloid PET imaging in Alzheimer’s disease: a comparison of three radiotracers. Eur J Nucl Med Mol Imaging. 2014;41(7):1398–407.CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Klunk WE, Wang Y, Huang GF, Debnath ML, Holt DP, Shao L, et al. The binding of 2-(4′-methylaminophenyl)benzothiazole to postmortem brain homogenates is dominated by the amyloid component. The Journal of neuroscience : the official journal of the Society for Neuroscience. 2003;23(6):2086–92.Google Scholar
  52. 52.
    Price JC, Klunk WE, Lopresti BJ, Lu X, Hoge JA, Ziolko SK, et al. Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh compound-B. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism. 2005;25(11):1528–47.CrossRefGoogle Scholar
  53. 53.
    Zhang W, Kung MP, Oya S, Hou C, Kung HF. 18F-labeled styrylpyridines as PET agents for amyloid plaque imaging. Nucl Med Biol. 2007;34(1):89–97.CrossRefPubMedGoogle Scholar
  54. 54.
    Clark CM, Schneider JA, Bedell BJ, Beach TG, Bilker WB, Mintun MA, et al. Use of florbetapir-PET for imaging beta-amyloid pathology. JAMA. 2011;305(3):275–83.CrossRefPubMedGoogle Scholar
  55. 55.
    Ikonomovic MD, Klunk WE, Abrahamson EE, Mathis CA, Price JC, Tsopelas ND, et al. Post-mortem correlates of in vivo PiB-PET amyloid imaging in a typical case of Alzheimer’s disease. Brain. 2008;131(Pt 6):1630–45.CrossRefPubMedPubMedCentralGoogle Scholar
  56. 56.
    Choi SR, Schneider JA, Bennett DA, Beach TG, Bedell BJ, Zehntner SP, et al. Correlation of amyloid PET ligand florbetapir F 18 binding with Abeta aggregation and neuritic plaque deposition in postmortem brain tissue. Alzheimer Dis Assoc Disord. 2012;26(1):8–16.CrossRefPubMedPubMedCentralGoogle Scholar
  57. 57.
    Curtis C, Gamez JE, Singh U, Sadowsky CH, Villena T, Sabbagh MN, et al. Phase 3 trial of flutemetamol labeled with radioactive fluorine 18 imaging and neuritic plaque density. JAMA Neurol. 2015;72(3):287–94.CrossRefPubMedGoogle Scholar
  58. 58.
    Ong KT, Villemagne VL, Bahar-Fuchs A, Lamb F, Langdon N, Catafau AM, et al. Abeta imaging with 18F-florbetaben in prodromal Alzheimer’s disease: a prospective outcome study. J Neurol Neurosurg Psychiatry. 2015;86(4):431–6.CrossRefPubMedGoogle Scholar
  59. 59.
    Villemagne VL, Mulligan RS, Pejoska S, Ong K, Jones G, O'Keefe G, et al. Comparison of 11C-PiB and 18F-florbetaben for Abeta imaging in ageing and Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2012;39(6):983–9.CrossRefPubMedGoogle Scholar
  60. 60.
    Archer HA, Edison P, Brooks DJ, Barnes J, Frost C, Yeatman T, et al. Amyloid load and cerebral atrophy in Alzheimer’s disease: an 11C-PIB positron emission tomography study. Ann Neurol. 2006;60(1):145–7.CrossRefPubMedGoogle Scholar
  61. 61.•
    Yeo JM, Waddell B, Khan Z, Pal S. A systematic review and meta-analysis of (18)F-labeled amyloid imaging in Alzheimer’s disease. Alzheimers Dement (Amst). 2015;1(1):5–13. In this systemic review and meta-analysis, the authors have included 19 studies investigating 682 AD patients. They calculated pooled weighted sensitivity, specificity, and odds ratios for each of 18F-labeled amyloid tracer.Google Scholar
  62. 62.
    Laforce R Jr, Rabinovici GD. Amyloid imaging in the differential diagnosis of dementia: review and potential clinical applications. Alzheimers Res Ther. 2011;3(6):31.CrossRefPubMedPubMedCentralGoogle Scholar
  63. 63.
    Johnson KA, Minoshima S, Bohnen NI, Donohoe KJ, Foster NL, Herscovitch P, et al. Update on appropriate use criteria for amyloid PET imaging: dementia experts, mild cognitive impairment, and education. Amyloid imaging task force of the Alzheimer’s Association and Society for Nuclear Medicine and Molecular Imaging. Alzheimers Dement. 2013;9(4):e106–9.CrossRefPubMedGoogle Scholar
  64. 64.
    Johnson KA, Minoshima S, Bohnen NI, Donohoe KJ, Foster NL, Herscovitch P, et al. 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. 2013;(1):9, e-1–e16.Google Scholar
  65. 65.
    Laforce R, Rosa-Neto P, Soucy JP, Rabinovici GD, Dubois B, Gauthier S. Canadian consensus guidelines on use of amyloid imaging in Canada: update and future directions from the specialized task force on amyloid imaging in Canada. Can J Neurol Sci. 2016;43(4):503–12.CrossRefPubMedGoogle Scholar
  66. 66.
    Jagust WJ, Bandy D, Chen K, Foster NL, Landau SM, Mathis CA, et al. The Alzheimer’s disease neuroimaging initiative positron emission tomography core. Alzheimers Dement. 2010;6(3):221–9.CrossRefPubMedPubMedCentralGoogle Scholar
  67. 67.
    Rabinovici GD. Impact of amyloid PET on patient management: early results from the IDEAS study. AAIC; London2017.Google Scholar
  68. 68.
    Landau SM, Fero A, Baker SL, Koeppe R, Mintun M, Chen K, et al. Measurement of longitudinal beta-amyloid change with 18F-florbetapir PET and standardized uptake value ratios. J Nucl Med. 2015;56(4):567–74.CrossRefPubMedPubMedCentralGoogle Scholar
  69. 69.
    Ossenkoppele R, Jansen WJ, Rabinovici GD, Knol DL, van der Flier WM, van Berckel BN, et al. Prevalence of amyloid PET positivity in dementia syndromes: a meta-analysis. JAMA. 2015;313(19):1939–49.CrossRefPubMedPubMedCentralGoogle Scholar
  70. 70.
    Harkins K, Sankar P, Sperling R, Grill JD, Green RC, Johnson KA, et al. Development of a process to disclose amyloid imaging results to cognitively normal older adult research participants. Alzheimers Res Ther. 2015;7(1):26.CrossRefPubMedPubMedCentralGoogle Scholar
  71. 71.
    Grill JD, Apostolova LG, Bullain S, Burns JM, Cox CG, Dick M, et al. Communicating mild cognitive impairment diagnoses with and without amyloid imaging. Alzheimers Res Ther. 2017;9(1):35.CrossRefPubMedPubMedCentralGoogle Scholar
  72. 72.
    Braak H, Braak E. Frequency of stages of Alzheimer-related lesions in different age categories. Neurobiol Aging. 1997;18(4):351–7.CrossRefPubMedGoogle Scholar
  73. 73.
    Nelson PT, Alafuzoff I, Bigio EH, Bouras C, Braak H, Cairns NJ, et al. Correlation of Alzheimer disease neuropathologic changes with cognitive status: a review of the literature. J Neuropathol Exp Neurol. 2012;71(5):362–81.CrossRefPubMedPubMedCentralGoogle Scholar
  74. 74.
    Bierer LM, Hof PR, Purohit DP, Carlin L, Schmeidler J, Davis KL, et al. Neocortical neurofibrillary tangles correlate with dementia severity in Alzheimer’s disease. Arch Neurol. 1995;52(1):81–8.CrossRefPubMedGoogle Scholar
  75. 75.
    Whitwell JL, Josephs KA, Murray ME, Kantarci K, Przybelski SA, Weigand SD, et al. MRI correlates of neurofibrillary tangle pathology at autopsy: a voxel-based morphometry study. Neurology. 2008;71(10):743–9.CrossRefPubMedPubMedCentralGoogle Scholar
  76. 76.
    Okamura N, Harada R, Furukawa K, Furumoto S, Tago T, Yanai K, et al. Advances in the development of tau PET radiotracers and their clinical applications. Ageing Res Rev. 2016;30:107–13.CrossRefPubMedGoogle Scholar
  77. 77.•
    Olsson B, Lautner R, Andreasson U, Ohrfelt A, Portelius E, Bjerke M, et al. CSF and blood biomarkers for the diagnosis of Alzheimer’s disease: a systematic review and meta-analysis. Lancet Neurol. 2016;15(7):673–84. This tour de force review and meta-analysis of 231 articles containing 15,699 patients with AD and 13,018 controls identified the most consistent AD biomarkers as CSF T-tau, P-tau, Aβ42, and neurofilamentGoogle Scholar
  78. 78.
    Molinuevo JL, Blennow K, Dubois B, Engelborghs S, Lewczuk P, Perret-Liaudet A, et al. The clinical use of cerebrospinal fluid biomarker testing for Alzheimer’s disease diagnosis: a consensus paper from the Alzheimer’s biomarkers standardization initiative. Alzheimers Dement. 2014;10(6):808–17.CrossRefPubMedGoogle Scholar
  79. 79.•
    Ritchie C, Smailagic N, Noel-Storr AH, Ukoumunne O, Ladds EC, Martin S. CSF tau and the CSF tau/ABeta ratio for the diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev. 2017;3:Cd010803. This Cochrane Systemic Review urged caution in the use of CSF tau and CSF tau/ABeta ratio in patients with MCI due to risk of misdiagnosis or overdiagnosisGoogle Scholar
  80. 80.
    Perret-Liaudet A, Pelpel M, Tholance Y, Dumont B, Vanderstichele H, Zorzi W, et al. Risk of Alzheimer’s disease biological misdiagnosis linked to cerebrospinal collection tubes. J Alzheimers Dis. 2012;31(1):13–20.PubMedGoogle Scholar
  81. 81.
    Irwin DJ, Lleo A, Xie SX, McMillan CT, Wolk DA, Lee EB, et al. Ante mortem cerebrospinal fluid tau levels correlate with postmortem tau pathology in frontotemporal lobar degeneration. Ann Neurol. 2017;82(2):247–58.CrossRefPubMedGoogle Scholar
  82. 82.
    Scherling CS, Hall T, Berisha F, Klepac K, Karydas A, Coppola G, et al. Cerebrospinal fluid neurofilament concentration reflects disease severity in frontotemporal degeneration. Ann Neurol. 2014;75(1):116–26.CrossRefPubMedPubMedCentralGoogle Scholar
  83. 83.
    Meeter LH, Kaat LD, Rohrer JD, van Swieten JC. Imaging and fluid biomarkers in frontotemporal dementia. Nat Rev Neurol 2017;13(7):406–419.Google Scholar
  84. 84.
    O'Bryant SE, Mielke MM, Rissman RA, Lista S, Vanderstichele H, Zetterberg H, et al. Blood-based biomarkers in Alzheimer disease: current state of the science and a novel collaborative paradigm for advancing from discovery to clinic. Alzheimers Dement. 2017;13(1):45–58.CrossRefPubMedGoogle Scholar

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© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Nasim Sheikh-Bahaei
    • 1
  • Seyed Ahmad Sajjadi
    • 2
  • Aimee L. Pierce
    • 2
    Email author
  1. 1.Department of RadiologyUniversity of Cambridge School of Clinical MedicineCambridgeUK
  2. 2.Department of NeurologyUniversity of CaliforniaIrvineUSA

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