CSF biomarkers and amyloid PET: concordance and diagnostic accuracy in a MCI cohort

Abstract

Brain amyloid deposition is one of the main hallmarks of Alzheimer’s disease (AD) and two approaches are available for assessing amyloid pathology in vivo: cerebrospinal fluid (CSF) biomarkers levels and amyloid load visualized by amyloid beta positron emission tomography imaging (Amy-PET) probes. We aimed to investigate the concordance between CSF biomarkers and Amy-PET in a memory clinic cohort. Moreover, using a proper clinical follow-up, we wanted to assess the diagnostic accuracy of CSF and PET biomarkers in predicting the progression of patients with mild cognitive impairment (MCI) to AD dementia. We included 31 MCI patients who underwent [18F]florbetaben PET and CSF sampling (Aβ1–42, t-Tau, p-Tau). A semiquantitative visual scan assessment was used to quantify amyloid deposition in 5 brain regions, rating from 1 (negative), to 2 and 3 (positive). CSF biomarkers were considered abnormal if: Aβ1–42 < 600 pg/ml, p-Tau/Aβ1–42 > 0.08 and t-Tau/Aβ1–42 > 0.52. We also applied less lenient cutoffs of 550 pg/ml and 450 pg/ml for Aβ1–42. The concordance rate was 77% between Amy-PET and CSF Aβ1–42 levels, and 89% between Amy-PET and p-Tau/Aβ1–42 and t-Tau/Aβ1–42. According to the clinical follow-up, Amy-PET (sensitivity [SE] 93.7%, specificity [SP] 80%) exhibited the best diagnostic accuracy in discriminating AD from non-AD, followed by p-Tau/Aβ1–42 ratio and t-Tau/Aβ1–42 ratio (SE 93.7%, SP 66.6%), and Aβ1–42 levels (SE 81%, SP 60%). The regional uptake of [18F]florbetaben PET in the precuneus and the striatum showed the best SP (86.6%). In discordant cases, the clinical diagnosis was most often in agreement with PET results. In general, concordance between CSF biomarkers and Amy-PET was good, especially when the ratios between CSF amyloid and Tau biomarkers were used. However, Amy-PET proved to be superior to CSF Aβ1–42 in terms of diagnostic accuracy for AD, with the possibility to further increase its specificity by focusing the analysis in specific areas such as the precuneus/posterior cingulate cortex and the striatum.

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

Fig. 1

References

  1. 1.

    Kuller LH, Lopez OL (2011) Dementia and Alzheimer’s disease: a new direction. The 2010 Jay L. Foster Memorial Lecture. Alzheimers Dement 7(5):540–550

    Article  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Braak H, Braak E (1991) Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 82(4):239–259

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Braak H, Alafuzoff I, Arzberger T, Kretzschmar H, Del Tredici K (2006) Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol 112:389–404

    Article  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Morris GP, Clark IA, Vissel B (2014) Inconsistencies and controversies surrounding the amyloid hypothesis of Alzheimer’s disease. Acta Neuropathol Commun 2:135

    PubMed  PubMed Central  Google Scholar 

  5. 5.

    Jack CR Jr, Knopman DS, Jagust WJ, Petersen RC, Aisen PS, Shaw LM, Vemuri P, Wiste HJ, Weigand SD, Lesnick TG, Pankratz VS, Donohue MC, Trojanowski JQ (2013) Tracking pathophysiological processes in Alzheimer’s disease: An updated hypothetical model of dynamic biomarkers. Lancet Neurol 12:207–216

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Herukka SK, Simonsen AH, Andreasen N, Baldeiras I, Bjerke M, Blennow K, Engelborghs S, Frisoni GB, Gabryelewicz T, Galluzzi S, Handels R, Kramberger MG, Kulczyńska A, Molinuevo JL, Mroczko B, Nordberg A, Oliveira CR, Otto M, Rinne JO, Rot U, Saka E, Soininen H, Struyfs H, Suardi S, Visser PJ, Winblad B, Zetterberg H, Waldemar G (2017) Recommendations for cerebrospinal fluid Alzheimer’s disease biomarkers in the diagnostic evaluation of mild cognitive impairment. Alzheimers Dement 13(3):285–295

    Article  PubMed  Google Scholar 

  7. 7.

    Blennow K, Zetterberg H, Fagan AM (2012) Fluid biomarkers in Alzheimer disease. Cold Spring Harb Perspect Med 2012 Sep 1:2–9

    Google Scholar 

  8. 8.

    de Leon MJ, DeSanti S, Zinkowski R, Mehta PD, Pratico D, Segal S, Rusinek H, Li J, Tsui W, Saint Louis LA, Clark CM, Tarshish C, Li Y, Lair L, Javier E, Rich K, Lesbre P, Mosconi L, Reisberg B, Sadowski M, DeBernadis JF, Kerkman DJ, Hampel H, Wahlund LO, Davies P (2006) Longitudinal CSF and MRI biomarkers improve the diagnosis of mild cognitive impairment. Neurobiol Aging 27:394–401

    Article  CAS  PubMed  Google Scholar 

  9. 9.

    Ritchie C, Smailagic N, Noel-Storr AH, Takwoingi Y, Flicker L, Mason SE, McShane R (2014) Plasma and cerebrospinal fluid amyloid beta for the diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev 10:(6)

    Google Scholar 

  10. 10.

    Driscoll I, Troncoso JC, Rudow G, Sojkova J, Zhou Y, Kraut MA, Ferrucci L, Mathis CA, Klunk WE, O’Brien RJ, Davatzikos C, Wong DF, Resnick SM (2012) Correspondence between in vivo (11)C-PiB-PET amyloid imaging and postmortem, region-matched assessment of plaques. Acta Neuropathol 124:823–831

    Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Sabri O, Seibyl J, Rowe C, Barthel H (2015) Beta-amyloid imaging with florbetaben. Clin Transl Imaging 3(1):13–26

    Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Clifford R. Jack CR Jr, Barrio JR, Kepe V (2013) Cerebral amyloid PET imaging in Alzheimer’s disease. Acta Neuropathol Acta Neuropathol 126(5):643–657

    Article  CAS  Google Scholar 

  13. 13.

    Waldemar G, Wallin A, Wallin ÅK, Wiltfang J, Wolk DA, Zboch M, Zetterberg H (2015) prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis. JAMA 313(19):1924–1938

    Article  PubMed  Google Scholar 

  14. 14.

    Ossenkoppele R, Jansen WJ, Rabinovici GD, Knol DL, van der Flier WM, van Berckel BN, Scheltens P, Visser PJ, Amyloid PETS, Verfaillie SC, Zwan MD, Adriaanse SM, Lammertsma AA, Barkhof F, Jagust WJ, Miller BL, Rosen HJ, Landau SM, Villemagne VL, Rowe CC, Lee DY, Na DL, Seo SW, Sarazin M, Roe CM, Sabri O, Barthel H, Koglin N, Hodges J, Leyton CE, Vandenberghe R, van Laere K, Drzezga A, Forster S, Grimmer T, Sánchez-Juan P, Carril JM, Mok V, Camus V, Klunk WE, Cohen AD, Meyer PT, Hellwig S, Newberg A, Frederiksen KS, Fleisher AS, Mintun MA, Wolk DA, Nordberg A, Rinne JO, Chételat G, Lleo A, Blesa R, Fortea J, Madsen K, Rodrigue KM, Brooks DJ (2015) Prevalence of Amyloid PET Positivity in Dementia Syndromes: A Meta-analysis. JAMA 313(19):1939–1949

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Guerra UP, Nobili FM, Padovani A, Perani D, Pupi A, Sorbi S, Trabucchi M (2015) Recommendations from the Italian Interdisciplinary Working Group (AIMN, AIP, SINDEM) for the utilization of amyloid imaging in clinical practice. Neurol Sci 36(6):1075–1081

    Article  PubMed  Google Scholar 

  16. 16.

    Johnson KA, Minoshima S, Bohnen NI, Donohoe KJ, Foster NL, Herscovitch P, Karlawish JH, Rowe CC, Carrillo MC, Hartley DM, Hedrick S, Pappas V, Thies WH; Alzheimer’s Association; Society of Nuclear Medicine and Molecular Imaging; Amyloid Imaging Taskforce (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. J Nucl Med 54(3):476–490

  17. 17.

    Dubois B, Feldman HH, Jacova C, Hampel H, Molinuevo JL, Blennow K, DeKosky ST, Gauthier S, Selkoe D, Bateman R, Cappa S, Crutch S, Engelborghs S, Frisoni GB, Fox NC, Galasko D, Habert MO, Jicha GA, Nordberg A, Pasquier F, Rabinovici G, Robert P, Rowe C, Salloway S, Sarazin M, Epelbaum S, de Souza LC, Vellas B, Visser PJ, Schneider L, Stern Y, Scheltens P, Cummings JL (2014) Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol 13(6):614–629

    Article  PubMed  Google Scholar 

  18. 18.

    McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH (2011) The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute onAging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7:263–269

    Article  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Leuzy A, Chiotis K, Hasselbalch SG, Rinne JO, de Mendonça A, Otto M, Lleó A, Castelo-Branco M, Santana I, Johansson J, Anderl-Straub S, von Arnim CA, Beer A, Blesa R, Fortea J, Herukka SK, Portelius E, Pannee J, Zetterberg H, Blennow K, Nordberg A (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 

  20. 20.

    Zwan M, van Harten A, Ossenkoppele R, Bouwman F, Teunissen C, Adriaanse S, Lammertsma A, Scheltens P, van Berckel B, van der Flier W (2014) Concordance between cerebrospinal fluid biomarkers and [11C]PIB PET in a memory clinic cohort. J Alzheimers Dis 41(3):801–807

    CAS  Article  PubMed  Google Scholar 

  21. 21.

    Palmqvist S, Mattsson N, Hansson O, Alzheimer’s Disease Neuroimaging Initiative (2106) Cerebrospinal fluid analysis detects cerebral amyloid-β accumulation earlier than positron emission. tomography Brain 139:1226–1236

    Google Scholar 

  22. 22.

    Leuzy A, Carter SF, Chiotis K, Almkvist O, Wall A, Nordberg A (2015) Concordance and diagnostic accuracy of [11C]PIB PET and cerebrospinal fluid biomarkers in a sample of patients with mild cognitive impairment and Alzheimer’s Disease. J Alzheimers Dis 45(4):1077–1088

    CAS  Article  PubMed  Google Scholar 

  23. 23.

    Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E (1999) Mild cognitive impairment: Clinical characterization and outcome. Arch Neurol 56:303–308

    CAS  Article  PubMed  Google Scholar 

  24. 24.

    Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, Gamst A, Holtzman DM, Jagust WJ, Petersen RC, Snyder PJ, Carrillo MC, Thies B, Phelps CH (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 7:271–279

    Article  Google Scholar 

  25. 25.

    McKhann G, Drachman D, Folstein M, Katzman R, Stadlan EM (1984) Clinical diagnosis of Alzheimer’s dis- ease: Report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 34:939–944

    CAS  Article  PubMed  Google Scholar 

  26. 26.

    Rascovsky K, Hodges JR, Knopman D, Mendez MF, Kramer JH, Neuhaus J, van Swieten JC, Seelaar H, Dopper EG, Onyike CU, Hillis AE, Josephs KA, Boeve BF, Kertesz A, Seeley WW, Rankin KP, Johnson JK, Gorno-Tempini ML, Rosen H, Prioleau-Latham CE, Lee A, Kipps CM, Lillo P, Piguet O, Rohrer JD, Rossor MN, Warren JD, Fox NC, Galasko D, Salmon DP, Black SE, Mesulam M, Weintraub S, Dickerson BC, Diehl-Schmid J, Pasquier F, Deramecourt V, Lebert F, Pijnenburg Y, Chow TW, Manes F, Grafman J, Cappa SF, Freedman M, Grossman M, Miller BL (2011) Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain 134(9):2456–2477

    Article  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Armstrong MJ, Litvan I, Lang AE, Bak TH, Bhatia KP, Borroni B, Boxer AL, Dickson DW, Grossman M, Hallett M, Josephs KA, Kertesz A, Lee SE, Miller BL, Reich SG, Riley DE, Tolosa E, Tröster AI, Vidailhet M, Weiner WJ (2013) Criteria for the diagnosis of corticobasal degeneration. Neurology 2013 Jan 29(5):496–503 80(

    Article  Google Scholar 

  28. 28.

    McKeith IG, Dickson DW, Lowe J, Emre M, O’Brien JT, Feldman H, Cummings J, Duda JE, Lippa C, Perry EK, Aarsland D, Arai H, Ballard CG, Boeve B, Burn DJ, Costa D, Del Ser T, Dubois B, Galasko D, Gauthier S, Goetz CG, Gomez-Tortosa E, Halliday G, Hansen LA, Hardy J, Iwatsubo T, Kalaria RN, Kaufer D, Kenny RA, Korczyn A, Kosaka K, Lee VM, Lees A, Litvan I, Londos E, Lopez OL, Minoshima S, Mizuno Y, Molina JA, Mukaetova-Ladinska EB, Pasquier F, Perry RH, Schulz JB, Trojanowski JQ, Yamada M, Consortium on DLB (2005) Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology 65(12):1863–72

    CAS  Article  PubMed  Google Scholar 

  29. 29.

    Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, Ogar JM, Rohrer JD, Black S, Boeve BF, Manes F, Dronkers NF, Vandenberghe R, Rascovsky K, Patterson K, Miller BL, Knopman DS, Hodges JR, Mesulam MM, Grossman M (2011) Classification of primary progressive aphasia and its variants. Neurology 76(11):1006–1014

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Duits FH, Teunissen CE, Bouwman FH, Visser PJ, Mattsson N, Zetterberg H, Blennow K, Hansson O, Minthon L, Andreasen N, Marcusson J, Wallin A, Rikkert MO, Tsolaki M, Parnetti L, Herukka SK, Hampel H, De Leon MJ, Schröder J, Aarsland D, Blankenstein MA, Scheltens P, van der Flier WM (2014) The cerebrospinal fluid “Alzheimer profile”: easily said, but what does it mean? Alzheimers Dement 10(6):713–723

    Article  PubMed  Google Scholar 

  31. 31.

    Barthel H, Luthardt J, Becker G, Patt M, Hammerstein E, Hartwig K, Eggers B, Sattler B, Schildan A, Hesse S, Meyer PM, Wolf H, Zimmermann T, Reischl J, Rohde B, Gertz HJ, Reininger C, Sabri O (2011) Individualized quantification of brain beta-amyloid burden: results of a proof of mechanism phase 0 florbetaben PET trial in patients with Alzheimer’s disease and healthy controls. Eur J Nucl Med Mol Imaging 38:1702–1711

    CAS  Article  PubMed  Google Scholar 

  32. 32.

    Barthel H, Gertz HJ, Dresel S, Peters O, Bartenstein P, Buerger K, Hiemeyer F, Wittemer-Rump SM, Seibyl J, Reininger C, Sabri O, Florbetaben Study Group (2011) Cerebral amyloid-beta PET with florbetaben (18F) in patients with Alzheimer’s disease and healthy controls: a multicentre phase 2 diagnostic study. Lancet Neurol 10:424–435

    CAS  Article  PubMed  Google Scholar 

  33. 33.

    Palmqvist S, Zetterberg H, Mattsson N, Johansson P; Alzheimer’s Disease Neuroimaging Initiative, Minthon L, Blennow K, Olsson M, Hansson O, Swedish BioFINDER Study Group (2015) Detailed comparison of amyloid PET and CSF biomarkers for identifying early Alzheimer disease. Neurology 85(14):1240–1249

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Doecke JD, Rembach A, Villemagne VL, Varghese S, Rainey-Smith S, Sarros S, Evered LA, Fowler CJ, Pertile KK, Rumble RL, Trounson B, Taddei K, Laws SM, Macaulay SL, Bush AI, Ellis KA, Martins R, Ames D, Silbert B, Vanderstichele H, Masters CL, Darby DG, Li QX, Collins S, AIBL Research Group.Concordance (2018) Between Cerebrospinal Fluid Biomarkers with Alzheimer’s Disease Pathology Between Three Independent Assay Platforms. J Alzheimers Dis 62(3):965–992

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Mattsson N, Andreasson U, Persson S, Arai H, Batish SD, Bernardini S, Bocchio-Chiavetto L, Blankenstein MA, Car-rillo MC, Chalbot S, Coart E, Chiasserini D, Cutler N, Dahlfors G, Duller S, Fagan AM, Forlenza O, Frisoni GB, Galasko D, Galimberti D, Hampel H, Handberg A, Heneka MT, Herskovits AZ, Herukka SK, Holtzman DM, Humpel C, Hyman BT, Iqbal K, Jucker M, Kaeser SA, Kaiser E, Kapaki E, Kidd D, Klivenyi P, Knudsen CS, Kummer MP, Lui J, Llado A, Lewczuk P, Li QX, Martins R, Masters C, McAuliffe J, Mercken M, Moghekar A, Molinuevo JL, Montine TJ, Nowatzke W, O’Brien R, Otto M, Paraskevas GP, Parnetti L, Petersen RC, Prvulovic D, de Reus HP, Rissman RA, Scarpini E, Stefani A, Soininen H, Schroder J, Shaw LM, Skinningsrud A, Skrogstad B, Spreer A, Talib L, Teunissen C, Trojanowski JQ, Tumani H, Umek RM, Van Broeck B, Vanderstichele H, Vecsei L, Verbeek MM, Windisch M, Zhang J, Zetterberg H, Blennow K (2011) The Alzheimer’s Association external quality control program for cerebrospinal fluid biomarkers. Alzheimers Dement 7:386–395

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Bjerke M, Portelius E, Minthon L, Wallin A, Anckarsater H, Anckarsater R, Andreasen N, Zetterberg H, Andreasson U, Blennow K (2010) Confounding factors influencing amyloid Beta concentration in cerebrospinal fluid. Int J Alzheimers Dis

  37. 37.

    Ooms S, Overeem S, Besse K, Rikkert MO, Verbeek M, Claassen JA (2014) Effect of 1 night of total sleep deprivation on cerebrospinal fluid beta-amyloid 42 in healthy middle-aged men: A randomized clinical trial. JAMA Neurol 71(8):971–977

    Article  PubMed  Google Scholar 

  38. 38.

    Grothe MJ, Barthel H, Sepulcre J, Dyrba M, Sabri O, Teipel SJ, Alzheimer’s Disease Neuroimaging Initiative (2017) vivo staging of regional amyloid deposition Neurology 89(20):2031–2038

    CAS  PubMed  Google Scholar 

  39. 39.

    Stricker NH, Dodge HH, Dowling NM, Han SD, Erosheva EA, Jagust WJ, Alzheimer’s DiseaseNeuroimaging Initiative (2012) CSF biomarker associations with change in hippocampal volume and precuneus thickness: implications for the Alzheimer’s pathological cascade. Brain Imaging Behav 6(4):599–609

    Article  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Ikonomovic MD, Klunk WE, Abrahamson EE, Wuu J, Mathis CA, Scheff SW, Mufson EJ, DeKosky ST (2011) Precuneus amyloid burden is associated with reduced cholinergic activity in Alzheimer disease. Neurology 77(1):39–47

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Hanseeuw BJ, Betensky RA, Mormino EC, Schultz AP, Sepulcre J, Becker JA, Jacobs HIL, Buckley RF, LaPoint MR, Vannini P, Donovan NJ, Chhatwal JP, Marshall GA, Papp KV, Amariglio RE, Rentz DM, Sperling RA, Johnson KA; Alzheimer’s Disease Neuroimaging Initiative; Harvard Aging Brain Study (2018) PET staging of amyloidosis using striatum. Alzheimers Dement 14(10):1281–1292

    Article  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, Holtzman DM, Jagust W, Jessen F, Karlawish J, Liu E, Molinuevo JL, Montine T, Phelps C, Rankin KP, Rowe CC, Scheltens P, Siemers E, Snyder HM, Sperling R, Contributors (2018) NIA-AA research framework: toward a biological definition of alzheimer’s disease. Alzheimers Dement 14(4):535–562

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This research was supported in part by a Piramal Pharma Solutions grant. The funding source had no role in the study design, data collection, data analysis, data interpretation or writing of this study.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Marco Spallazzi.

Ethics declarations

Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

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

Informed consent

Informed consent obtained from all patients.

Additional information

Publisher’s Note

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

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Spallazzi, M., Barocco, F., Michelini, G. et al. CSF biomarkers and amyloid PET: concordance and diagnostic accuracy in a MCI cohort. Acta Neurol Belg 119, 445–452 (2019). https://doi.org/10.1007/s13760-019-01112-8

Download citation

Keywords

  • MCI
  • CSF biomarkers
  • Amyloid PET
  • Posterior cingulate cortex
  • Striatum
  • Alzheimer’s disease