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Figure 1.
Cerebrospinal Fluid (CSF) Alzheimer Disease (AD) Biomarkers and Flutemetamol F 18–Labeled Positron Emission Tomography (PET)
Cerebrospinal Fluid (CSF) Alzheimer Disease (AD) Biomarkers and Flutemetamol F 18–Labeled Positron Emission Tomography (PET)

A, Concordance between visual and quantitative amyloid PET analysis. Composite standardized uptake value ratio (SUVR) of [18F]flutemetamol data in patients who were classified as negative (n = 149) or positive (n = 113) for amyloid findings with visual PET assessment are shown. The dotted line represents a cutoff of greater than 1.42 SUVR. Data points indicate individuals. B-F, Correlation of CSF AD biomarkers with [18F]flutemetamol PET status according to visual analysis. Levels of CSF β-amyloid (Aβ) 42 were analyzed with the classic INNOTEST (INC), modified INNOTEST (INM), EUROIMMUN (EI) and Meso Scale Discovery (MSD) assays. To calculate the CSF Aβ42:Aβ40 ratio, we used Aβ40 kits from the assay vendors Fujirebio (INC and INM), EUROIMMUN (EI), and Meso Scale Discovery (MSD). Levels of CSF total tau (T-tau) and phosphorylated tau (P-tau) were measured with the EI and INNOTEST assays, respectively. Receiver operating characteristic (ROC) curves were generated for Aβ42 level (B-F), the Aβ42:Aβ40 ratio (C [INC] and D [INM, EI, and MSD]), the Aβ42:T-tau ratio (C [INC] and E [INM, EI, and MSD]), and the Aβ42:P-tau ratio (C [INC] and F [INM, EI, and MSD]) to determine their accuracy in differentiating Aβ-negative (n = 149) and Aβ-positive (n = 113) visual readings. AUC indicates area under the ROC curve.

Figure 2.
Frequency Plots of Cerebrospinal Fluid (CSF) β-Amyloid (Aβ) 42 Levels and Aβ42:Aβ40 and Aβ42 to Phosphorylated Tau (P-tau) Ratios
Frequency Plots of Cerebrospinal Fluid (CSF) β-Amyloid (Aβ) 42 Levels and Aβ42:Aβ40 and Aβ42 to Phosphorylated Tau (P-tau) Ratios

Histograms of frequency distribution for CSF Aβ42 levels and the Aβ42:Aβ40 and Aβ42:P-tau ratios across groups with Aβ-positive (n = 113) and Aβ-negative (n = 149) visual ratings. Veritical dashed lines indicate cutoff points associated with the Youden J index. EI indicates EUROIMMUN; INC, classic INNOTEST; INM, modified INNOTEST; and MSD, Meso Scale Discovery.

Figure 3.
Separation of Populations by Visual Positron Emission Tomography (PET) Findings
Separation of Populations by Visual Positron Emission Tomography (PET) Findings

Separation of populations with positive and negative PET findings used cutoffs for cerebrospinal fluid (CSF) levels of β-amyloid (Aβ) 42 and the Aβ42:Aβ40 and Aβ42 to phosphorylated tau (P-tau) ratios. Scatterplots of CSF Aβ42 levels against Aβ40 and P-tau levels; Aβ42 was measured using the classic INNOTEST (INC), modified INNOTEST (INM), EUROIMMUN (EI), and Meso Scale Discovery (MSD) assays. Dotted lines indicate Youden J index cutoffs for CSF Aβ42 levels. Solid lines indicated Youden J index cutoffs for the CSF Aβ42:Aβ40 and Aβ42:P-tau ratios.

Table 1.  
Correlations Between Aβs Measured Using MS and Different Immunoassaysa
Correlations Between Aβs Measured Using MS and Different Immunoassaysa
Table 2.  
ROC Analysis of CSF Aβs for Distinguishing Abnormal From Normal Visual Reading Assessments of Flutemetamol F 18–Labeled PET
ROC Analysis of CSF Aβs for Distinguishing Abnormal From Normal Visual Reading Assessments of Flutemetamol F 18–Labeled PET
1.
Blennow  K, Mattsson  N, Schöll  M, Hansson  O, Zetterberg  H.  Amyloid biomarkers in Alzheimer’s disease.  Trends Pharmacol Sci. 2015;36(5):297-309.PubMedGoogle ScholarCrossref
2.
Ikonomovic  MD, Klunk  WE, Abrahamson  EE,  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):1630-1645.PubMedGoogle ScholarCrossref
3.
Strozyk  D, Blennow  K, White  LR, Launer  LJ.  CSF Aβ 42 levels correlate with amyloid-neuropathology in a population-based autopsy study.  Neurology. 2003;60(4):652-656.PubMedGoogle ScholarCrossref
4.
Tapiola  T, Alafuzoff  I, Herukka  SK,  et al.  Cerebrospinal fluid β-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain.  Arch Neurol. 2009;66(3):382-389.PubMedGoogle ScholarCrossref
5.
Wolk  DA, Grachev  ID, Buckley  C,  et al.  Association between in vivo fluorine 18-labeled flutemetamol amyloid positron emission tomography imaging and in vivo cerebral cortical histopathology.  Arch Neurol. 2011;68(11):1398-1403.PubMedGoogle ScholarCrossref
6.
Landau  SM, Lu  M, Joshi  AD,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Comparing positron emission tomography imaging and cerebrospinal fluid measurements of β-amyloid.  Ann Neurol. 2013;74(6):826-836.PubMedGoogle ScholarCrossref
7.
Mattsson  N, Insel  PS, Donohue  M,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Independent information from cerebrospinal fluid amyloid-β and florbetapir imaging in Alzheimer’s disease.  Brain. 2015;138(pt 3):772-783.PubMedGoogle ScholarCrossref
8.
Palmqvist  S, Zetterberg  H, Blennow  K,  et al.  Accuracy of brain amyloid detection in clinical practice using cerebrospinal fluid β-amyloid 42: a cross-validation study against amyloid positron emission tomography.  JAMA Neurol. 2014;71(10):1282-1289.PubMedGoogle ScholarCrossref
9.
Janelidze  S, Zetterberg  H, Mattsson  N,  et al; Swedish BioFINDER study group.  CSF Aβ42:Aβ40 and Aβ42:Aβ38 ratios: better diagnostic markers of Alzheimer disease.  Ann Clin Transl Neurol. 2016;3(3):154-165.PubMedGoogle ScholarCrossref
10.
Leuzy  A, Chiotis  K, Hasselbalch  SG,  et al.  Pittsburgh compound B imaging and cerebrospinal fluid amyloid-β in a multicentre European memory clinic study.  Brain. 2016;139(Pt 9):2540-2553.PubMedGoogle ScholarCrossref
11.
Vanderstichele  HM, Janelidze  S, Demeyer  L,  et al.  Optimized standard operating procedures for the analysis of cerebrospinal fluid Aβ42 and the ratios of Aβ isoforms using low protein binding tubes.  J Alzheimers Dis. 2016;53(3):1121-1132.PubMedGoogle ScholarCrossref
12.
Cullen  VC, Fredenburg  RA, Evans  C, Conliffe  PR, Solomon  ME.  Development and advanced validation of an optimized method for the quantitation of Aβ42 in human cerebrospinal fluid.  AAPS J. 2012;14(3):510-518.PubMedGoogle ScholarCrossref
13.
Bittner  T, Zetterberg  H, Teunissen  CE,  et al.  Technical performance of a novel, fully automated electrochemiluminescence immunoassay for the quantitation of β-amyloid (1-42) in human cerebrospinal fluid.  Alzheimers Dement. 2016;12(5):517-526.PubMedGoogle ScholarCrossref
14.
Pan  C, Korff  A, Galasko  D,  et al.  Diagnostic values of cerebrospinal fluid T-tau and Aβ42 using Meso Scale Discovery assays for Alzheimer’s disease.  J Alzheimers Dis. 2015;45(3):709-719.PubMedGoogle Scholar
15.
Vandijck  M, Moonen  R, Andreasson  U,  et al.  Correlation of the modified innotest β-amyloid 1-42 with a lc-ms:ms candidate reference method.  Alzheimers Dement. 2015;11(7)(suppl):385.PubMedGoogle ScholarCrossref
16.
Palmqvist  S, Zetterberg  H, Mattsson  N,  et al; Alzheimer’s Disease Neuroimaging Initiative; Swedish BioFINDER Study Group.  Detailed comparison of amyloid PET and CSF biomarkers for identifying early Alzheimer disease.  Neurology. 2015;85(14):1240-1249.PubMedGoogle ScholarCrossref
17.
Andreasen  N, Hesse  C, Davidsson  P,  et al.  Cerebrospinal fluid β-amyloid(1-42) in Alzheimer disease: differences between early- and late-onset Alzheimer disease and stability during the course of disease.  Arch Neurol. 1999;56(6):673-680.PubMedGoogle ScholarCrossref
18.
Clark  CM, Pontecorvo  MJ, Beach  TG,  et al; AV-45-A16 Study Group.  Cerebral PET with florbetapir compared with neuropathology at autopsy for detection of neuritic amyloid-β plaques: a prospective cohort study.  Lancet Neurol. 2012;11(8):669-678.PubMedGoogle ScholarCrossref
19.
Schreiber  S, Landau  SM, Fero  A, Schreiber  F, Jagust  WJ; Alzheimer’s Disease Neuroimaging Initiative.  Comparison of visual and quantitative florbetapir F 18 positron emission tomography analysis in predicting mild cognitive impairment outcomes.  JAMA Neurol. 2015;72(10):1183-1190.PubMedGoogle ScholarCrossref
20.
Leinenbach  A, Pannee  J, Dülffer  T,  et al; IFCC Scientific Division Working Group on CSF proteins.  Mass spectrometry–based candidate reference measurement procedure for quantification of amyloid-β in cerebrospinal fluid.  Clin Chem. 2014;60(7):987-994.PubMedGoogle ScholarCrossref
21.
Blennow  K, Hampel  H, Weiner  M, Zetterberg  H.  Cerebrospinal fluid and plasma biomarkers in Alzheimer disease.  Nat Rev Neurol. 2010;6(3):131-144.PubMedGoogle ScholarCrossref
22.
Pannee  J, Portelius  E, Minthon  L,  et al.  Reference measurement procedure for CSF amyloid β (Aβ)1-42 and the CSF Aβ1-42:Aβ1-40 ratio: a cross-validation study against amyloid PET.  J Neurochem. 2016;139(4):651-658.PubMedGoogle ScholarCrossref
23.
A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2014. http://www.R-project.org. Accessed September 17, 2016.
24.
Meng  XL, Rosenthal  R, Rubin  DB.  Comparing correlated correlation-coefficients.  Psychol Bull. 1992;111(1):172-175.Google ScholarCrossref
25.
Robin  X, Turck  N, Hainard  A,  et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves.  BMC Bioinformatics. 2011;12:77.PubMedGoogle ScholarCrossref
26.
Benaglia  T, Chauveau  D, Hunter  DR, Young  DS.  mixtools: an R package for analyzing finite mixture models.  J Stat Softw. 2009;32(6):1-29.Google ScholarCrossref
27.
Altman  DG.  Practical Statistics for Medical Research. London, England: Chapman & Hall:CRC; 1999.
28.
Buchhave  P, Minthon  L, Zetterberg  H, Wallin  AK, Blennow  K, Hansson  O.  Cerebrospinal fluid levels of β-amyloid 1-42, but not of tau, are fully changed already 5 to 10 years before the onset of Alzheimer dementia.  Arch Gen Psychiatry. 2012;69(1):98-106.PubMedGoogle ScholarCrossref
29.
De Meyer  G, Shapiro  F, Vanderstichele  H,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Diagnosis-independent Alzheimer disease biomarker signature in cognitively normal elderly people.  Arch Neurol. 2010;67(8):949-956.PubMedGoogle ScholarCrossref
30.
Zwan  MD, Ossenkoppele  R, Tolboom  N,  et al.  Comparison of simplified parametric methods for visual interpretation of 11C-Pittsburgh compound-B PET images.  J Nucl Med. 2014;55(8):1305-1307.PubMedGoogle ScholarCrossref
31.
Wang  MJ, Yi  S, Han  JY,  et al.  Analysis of cerebrospinal fluid and [11C]PIB PET biomarkers for Alzheimer’s disease with updated protocols.  J Alzheimers Dis. 2016;52(4):1403-1413.PubMedGoogle ScholarCrossref
32.
Hertze  J, Minthon  L, Zetterberg  H, Vanmechelen  E, Blennow  K, Hansson  O.  Evaluation of CSF biomarkers as predictors of Alzheimer’s disease: a clinical follow-up study of 4.7 years.  J Alzheimers Dis. 2010;21(4):1119-1128.PubMedGoogle ScholarCrossref
33.
Le Bastard  N, De Deyn  PP, Engelborghs  S.  Importance and impact of preanalytical variables on Alzheimer disease biomarker concentrations in cerebrospinal fluid.  Clin Chem. 2015;61(5):734-743.PubMedGoogle ScholarCrossref
34.
Toombs  J, Paterson  RW, Lunn  MP,  et al.  Identification of an important potential confound in CSF AD studies: aliquot volume.  Clin Chem Lab Med. 2013;51(12):2311-2317.PubMedGoogle ScholarCrossref
35.
Toombs  J, Paterson  RW, Nicholas  JM, Petzold  A, Schott  JM, Zetterberg  H.  The impact of Tween 20 on repeatability of amyloid β and tau measurements in cerebrospinal fluid.  Clin Chem Lab Med. 2015;53(12):e329-e332.PubMedGoogle ScholarCrossref
Original Investigation
December 2017

Concordance Between Different Amyloid Immunoassays and Visual Amyloid Positron Emission Tomographic Assessment

Author Affiliations
  • 1Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
  • 2Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
  • 3Biogen, Cambridge, Massachusetts
  • 4Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
  • 5Department of Molecular Neuroscience, University College London Institute of Neurology, Queen Square, London, England
  • 6Memory Clinic, Skåne University Hospital, Malmö, Sweden
JAMA Neurol. 2017;74(12):1492-1501. doi:10.1001/jamaneurol.2017.2814
Key Points

Question  How well do the core cerebrospinal fluid biomarkers of Alzheimer disease measured using different immunoassays agree with visual amyloid positron emission tomographic assessment?

Findings  In this study of 262 individuals with mild cognitive complaints, the cerebrospinal fluid Aβ42:Aβ40 or Aβ42:tau ratios from several newer assays showed improved accuracy for detection of cortical β-amyloid fibrils as measured by positron emission tomography.

Meaning  These findings support implementation of the cerebrospinal fluid Aβ42:Aβ40 and/or Aβ42:tau ratios as biomarkers of amyloid deposition in clinical practice and trials.

Abstract

Importance  Visual assessment of amyloid positron emission tomographic (PET) images has been approved by regulatory authorities for clinical use. Several immunoassays have been developed to measure β-amyloid (Aβ) 42 in cerebrospinal fluid (CSF). The agreement between CSF Aβ42 measures from different immunoassays and visual PET readings may influence the use of CSF biomarkers and/or amyloid PET assessment in clinical practice and trials.

Objective  To determine the concordance between CSF Aβ42 levels measured using 5 different immunoassays and visual amyloid PET analysis.

Design, Setting, and Participants  The study included 262 patients with mild cognitive impairment or subjective cognitive decline from the Swedish BioFINDER (Biomarkers for Identifying Neurodegenerative Disorders Early and Reliably) cohort (recruited from September 1, 2010, through December 31, 2014) who had undergone flutemetamol F 18 ([18F]flutemetamol)–labeled PET. Levels of CSF Aβ42 were analyzed using the classic INNOTEST and the newer modified INNOTEST, fully automated Lumipulse (FL), EUROIMMUN (EI), and Meso Scale Discovery (MSD) assays. Concentrations of CSF Aβ were assessed using an antibody-independent mass spectrometry–based reference measurement procedure.

Main Outcomes and Measures  The concordance of CSF Aβ42 levels and Aβ42:Aβ40 and Aβ42:tau ratios with visual [18F]flutemetamol PET status.

Results  Of 262 participants (mean [SD] age, 70.9 [5.5] years), 108 were women (41.2%) and 154 were men (58.8%). The mass spectrometry–derived Aβ42 values showed higher correlations with the modified Aβ42-INNOTEST (r = 0.97), Aβ42-FL (r = 0.93), Aβ42-EI (r = 0.93), and Aβ42-MSD (r = 0.95) assays compared with the classic Aβ42-INNOTEST assay (r = 0.88; P ≤ .01). The signal in the classic Aβ42-INNOTEST assay was partly quenched by recombinant Aβ1-40 peptide. However, the classic Aβ42-INNOTEST assay showed better concordance with visual [18F]flutemetamol PET status (area under the receiver operating characteristic curve [AUC], 0.92) compared with the newer assays (AUCs, 0.87-0.89; P ≤ .01). The accuracies of the newer assays improved significantly when Aβ42:Aβ40 (AUCs, 0.93-0.95; P ≤ .01), Aβ42 to total tau (T-tau) (AUCs, 0.94; P ≤ .05), or Aβ42 to phosphorylated tau (P-tau) (AUCs, 0.94-0.95; P ≤ .001) ratios were used. A combination of the Aβ42:Aβ40 ratio and T-tau or P-tau level did not improve the accuracy compared with the ratio alone.

Conclusions and Relevance  Concentrations of CSF Aβ42 derived from the new immunoassays (modified INNOTEST, FL, EI, and MSD) may correlate better with the antibody-independent mass spectrometry–based reference measurement procedure and may show improved agreement with visual [18F]flutemetamol PET assessment when using the Aβ42:Aβ40 or Aβ42:tau ratios. These findings suggest the benefit of implementing the CSF Aβ42:Aβ40 or Aβ42:tau ratios as a biomarker of amyloid deposition in clinical practice and trials.

Introduction

Cerebrospinal fluid (CSF) β-amyloid (Aβ) 42 and amyloid positron emission tomography (PET) have proved to have high diagnostic accuracy for Alzheimer disease (AD) years before the onset of clinical symptoms and are becoming an important part of the diagnostic workup.1 Both biomarkers have shown correlations with postmortem plaque measurements,2-5 and previous studies have indicated 80% to 90% agreement between CSF Aβ42 values and quantitative amyloid PET data.6-8 For most immunoassays, the concordance between the 2 biomarker modalities is further improved with the CSF Aβ42:Aβ40 ratio (compared with CSF Aβ42 level alone), probably because the ratio corrects for (1) interindividual variability in the overall Aβ production; (2) interindividual variability in the CSF turnover; (3) changes in global levels of all Aβ isoforms owing to non-AD–related abnormal findings, such as white matter lesions; and (4) variability owing to preanalytical factors.9-11

Several enzyme-linked immunosorbent assays (ELISAs) are commonly used for measurements of Aβ42 levels in CSF. In general, the precision of an immunoassay may be compromised by matrix interference when endogenous biological factors in the sample interact with the analyte of interest or nonspecifically bind to antibodies. Matrix interference affecting Aβ42 quantification has been reported for the initially developed INNOTEST Aβ42 assay12 but seems to be minimized in the newer Aβ immunoassays from EUROIMMUN, Fujirebio, Meso Scale Discovery, and Roche.13-15 A recent study suggested that the diagnostic accuracy of CSF Aβ biomarkers may vary depending on the assays used.16 More specifically, CSF Aβ42 measured with the classic INNOTEST (Fujirebio) kit17 performed better in distinguishing patients with early-stage AD from cognitively healthy control individuals than one of the newer immunoassays. At same time, using the CSF Aβ42:Aβ40 ratio improved the diagnostic accuracy of the newer EUROIMMUN (EI; EUROIMMUN) Aβ42 assay but not the classic Aβ42 INNOTEST assay.16 Another report9 demonstrated higher concordance between quantitative amyloid PET and the Aβ42:Aβ40 ratio compared with CSF Aβ42 level alone for the EI and Meso Scale Discovery (MSD; Meso Scale Discovery) assays.

In most of the studies that have compared amyloid PET with CSF Aβ42 levels, the quantification of regional and global amyloid PET ligand binding has used semiquantitative image assessments of standardized uptake value ratio (SUVR). In clinical practice, however, the standard approved by regulatory authorities is visual classification of scans on a binary scale as positive or negative for amyloid, with a negative finding indicating that AD is unlikely. Visual readings of PET images agree with PET SUVR values and with brain amyloid burden at autopsy.18,19 Nevertheless, concordance between the visual reading of PET and CSF Aβ42 measures from different immunoassays has not been established and may influence the use of amyloid PET and/or CSF analysis in clinical practice and trials. In the present study, we investigated the agreement between visual amyloid PET analysis and CSF Aβ42 measured using 5 different Aβ42 immunoassays or protocols (INNOTEST Aβ1-42 classical procedure, INNOTEST Aβ1-42 modified procedure, fully automated Lumipulse [FL; Fujirebio], EI Aβ1-42, and MSD AβN-42). For each of the 5 Aβ42 immunoassays, the performance of Aβ42 and the Aβ42:Aβ40, Aβ42 to total tau (T-tau), and Aβ42 to phosphorylated tau (P-tau) ratios were determined using visual assessment of flutemetamol F 18–labeled PET images as the criterion standard. Furthermore, an important advancement in the CSF biomarker field was the recent development of a mass spectrometry–based reference measurement procedure (RMP),20 which allows antibody-independent quantification of absolute CSF concentration of Aβ42 with high accuracy and is now considered to be the criterion standard method for CSF Aβ42 measurement.1 However, implementation of mass spectrometry in routine clinical laboratories is challenging owing to the complexity of the technology, the need for in-house method development and validation and personal training, and high costs. Herein, we explored correlation between CSF levels of amyloid biomarkers analyzed using immunoassays and antibody-independent mass spectrometry–based RMP.

Methods
Study Participants

The study population included 262 patients with mild cognitive impairment or subjective cognitive decline and no dementia from the prospective and longitudinal Swedish BioFINDER (Biomarkers for Identifying Neurodegenerative Disorders Early and Reliably) cohort (http://www.biofinder.se) who had undergone [18F]flutemetamol PET evaluation from September 1, 2010, through December 31, 2014. The diagnostic criteria and cohort characteristics are described in the eMethods and eTable 1 in the Supplement. The study was approved by the Regional Ethical Review Board in Lund, Sweden, and all study participants gave written informed consent to participate in the study.

CSF Sampling and Analysis

The procedure and analysis of CSF samples were conducted according to the Alzheimer Association Flowchart for CSF biomarkers.21 Lumbar CSF samples were collected at 3 memory clinics at the Skåne University Hospital in Lund and Malmö and Ängelholm Hospital in Sweden and analyzed according to a standardized protocol.8,21

We measured CSF Aβ42 levels using the EI Aβ1-42 and MSD AβN-42 according to the manufacturer’s instructions. We also measured CSF Aβ42 (1-42) with the INNOTEST kit (Fujirebio). For the latter assay, the classic procedure17 as described in the product’s package insert and a modified procedure that minimizes matrix interference effects were applied.15 The modifications included (1) dilution of conjugate 1 in conjugate diluent at 1:10 (classic procedure, 1:100 dilution), (2) addition of only 10 µL of samples or standards to the plate (classic procedure, 25 µL of samples or standards), and (3) incubation of samples or standards for 3 hours (classic procedure, 1 hour incubation). In addition, CSF concentrations of Aβ42 were determined using the fully automated FL assay, which is based on the modified INNOTEST procedure. We analyzed CSF Aβ40 levels with kits from Fujirebio (INNOTEST Aβ1-40), EI (Aβ1-40), and MSD (AβN-40) according to the manufacturer’s instructions, and the ratios with the corresponding CSF Aβ42 values (Aβ42:Aβ40) were calculated. We used the MSD electorchemiluminescence assay (Vplex; MSD) for multiplex detection of Aβ42, Aβ40, and Aβ38 levels. Cerebrospinal fluid T-tau and P-tau(181P) were quantified using EUROIMMUN and INNOTEST ELISA kits, respectively. These tau values and Aβ42 values from 5 different assays (classic INNOTEST, modified INNOTEST, FL, EI, and MSD) were used for the calculations of the CSF Aβ42:tau ratios.

Increasing concentrations of recombinant Aβ40 peptide (1-40 ng/mL) (rPeptide; Bogart) were added to 2 CSF samples with low and high Aβ42 concentrations. We measured Aβ42 levels in spiked samples using the classic and modified INNOTEST procedures and MSD assays. Finally, an antibody-independent mass spectrometry–based method was used to assess CSF concentrations of Aβ4220 using an RMP (Joint Committee for Traceability in Laboratory Medicine Database identification number C11RMP9) and Aβ4022 in a subgroup of 98 individuals. The [18F]flutemetamol PET imaging is described in the eMethods in the Supplement.

Statistical Analysis

We used SPSS (version 22; IBM), R (version 3.3.1),23 and MedCalc (version 16.8.4; MedCalc Software bvba) software for statistical analysis. Associations between ELISA and mass spectrometry–based biomarker concentrations were tested using Pearson and Spearman correlation coefficient analyses. Differences between the correlation coefficients were estimated using the Meng test for correlated correlation coefficients.24 Intermethod agreement between visual and quantitative [18F]flutemetamol PET assessments was estimated with the Cohen κ statistic. The accuracies of CSF biomarkers in detecting [18F]flutemetamol PET status were assessed using receiver operating characteristic (ROC) curve analysis and logistic regression models. Two areas under the ROC curve (AUCs) were compared using the DeLong test.25 We dichotomized the study participants into groups with normal and increased Aβ deposition based on the previously established [18F]flutemetamol SUVR cutoff of greater than 1.42.8 Cutoffs for CSF biomarkers were determined using the Youden J index and mixture modeling.26P < .05 was considered to be statistically significant.

Results
CSF Aβ Biomarkers: Associations Between ELISA and Mass Spectrometry Measurements

Of 262 participants (mean [SD] age, 70.9 [5.5] years), 108 were women (41.2%) and 154 were men (58.8%). To determine which of the immunoassays are more accurate in quantifying CSF levels of Aβ42, we studied associations between CSF concentrations of Aβ obtained with different immunoassays (classic INNOTEST and the newer modified INNOTEST, FL, EI, and MSD) and the antibody-independent mass spectrometry–based RMP for Aβ42 in a subgroup of 98 individuals. We found correlations between CSF levels of Aβ42 measured using ELISAs and mass spectrometry (r>0.88; Table 1). However, the correlation coefficients between different ELISA and mass spectrometry measurements varied significantly. Correlations with mass spectrometry–derived Aβ42 were greater for the new Aβ42 assays (r = 0.97 for the modified INNOTEST, r = 0.93 for FL, r = 0.93 for EI, and r = 0.95 for MSD) than the classic INNOTEST assay (r = 0.88). In contrast, the correlation between the mass spectrometry–derived Aβ42:Aβ40 ratio and the classic INNOTEST was significantly higher (r = 0.87) compared with the correlations between mass spectrometry–derived Aβ42:Aβ40 and the Aβ42 modified INNOTEST (r = 0.70), Aβ42-FL (r = 0.64), Aβ42-EI (r = 0.73), or Aβ42-MSD (r = 0.74) assays (Table 1).

Concordance Between Visual and Quantitative [18F]flutemetamol PET Assessments

With use of visual readings of [18F]flutemetamol PET, 113 patients (43.1%) were classified as Aβ positive and 149 patients (56.9%) as Aβ negative. When applying the SUVR cutoff, 132 patients (50.4%) showed abnormal amyloid deposition, whereas composite SUVR values were within the reference range in 130 patients (49.6%). The Cohen κ was 0.81, suggesting very good agreement between the visual and quantitative [18F]flutemetamol PET assessment methods.27 Visual and quantitative [18F]flutemetamol PET data disagreed in 25 cases (9.5%), of which 22 (8.4%) were Aβ positive based on the SUVR cutoff but Aβ negative based on visual analysis (Figure 1A).

Visual Aβ PET vs CSF AD Biomarker Assessments

We investigated how accurately CSF Aβ42 levels could predict visual [18F]flutemetamol PET assessment when using the commercially available classic Aβ42-INNOTEST assay or the newer modified Aβ42-INNOTEST, Aβ42-EI, and Aβ42-MSD asssays. The results of ROC curve analysis are shown in Table 2 and eTable 2 in the Supplement. We found that classic Aβ42-INNOTEST was more accurate than the newer assays (modified Aβ42-INNOTEST, Aβ42-EI, and Aβ42-MSD) in distinguishing individuals with normal and abnormal visual readings (Figure 1B). Next, we studied whether the Aβ42:Aβ40, Aβ42:T-tau, or Aβ42:P-tau ratios improved the accuracy of the 4 assays. For the classic Aβ42-INNOTEST, only the Aβ42:P-tau but not the Aβ42:Aβ40 or the Aβ42:T-tau ratios exhibited a significantly higher AUC than Aβ42 alone in predicting visual classification of [18F]flutemetamol PET (Table 2, eTable 2 in the Supplement, and Figure 1C). For all the newer assays (modified Aβ42-INNOTEST, Aβ42-EI, and Aβ42-MSD), all 3 ratios (ie, Aβ42:Aβ40, Aβ42:T-tau, and Aβ42:P-tau) were comparable and significantly more accurate than Aβ42 levels alone (Table 2, eTable 2 in the Supplement, and Figure 1D-F). The results for the Aβ42-FL assay were comparable to those of the modified Aβ42-INNOTEST assay and are shown in eFigure 1 in the Supplement. Furthermore, using logistic regression analysis, we found that a combination of the Aβ42:Aβ40 ratio and T-tau (AUCs, 0.92-0.95) or P-tau (AUCs, 0.92-0.93) for any of the 4 Aβ42 assays did not have better concordance with visual [18F]flutemetamol PET classification than the Aβ42:Aβ40 ratio alone (AUCs, 0.92-0.95; P > .14 when comparing the AUC of 2 ROC curves). The performance of T-tau and P-tau was similar in all the statistical tests and, therefore, only data for P-tau are presented hereinafter.

Cutoff for the Different Immunoassays

The Aβ42 levels in CSF are most often bimodally distributed,28 and more reliable cutoffs likely can be derived when biomarker levels show 2 clearly distinct populations.29 Frequency plots revealed improved bimodal separation of [18F]flutemetamol PET–positive and –negative populations based on the Aβ42:Aβ40 and Aβ42:P-tau ratios compared with the Aβ42 measurement alone when using the modified Aβ42-INNOTEST, Aβ42-EI, and Aβ42-MSD assays (Figure 2D-F, G-I, and J-L). This effect was less pronounced for the classic Aβ42-INNOTEST assay (Figure 2A-C). The cutoffs for each biomarker were determined based on the Youden J index in which visual read of [18F]flutemetamol PET was used as the outcome. Mixture modeling, which is independent of the standard of truth (ie, PET imaging results), produced similar cutoff values (Table 2). Analytical imprecision and within-participant variability may increase the risk for misclassification, especially when sensitivity and/or specificity markedly decrease around cutoff points. In our study, the trends for sensitivity and/or specificity near the cutoff points appeared to be less steep for the Aβ42:Aβ40 and Aβ42:P-tau ratios than for Aβ42 levels alone when Aβ42 was measured using the newer assays (modified Aβ42-INNOTEST, Aβ42-EI, or Aβ42-MSD) (eFigure 2B-D, F-H, and J-L in the Supplement), but this was not the case for the classic Aβ42-INNOTEST assay (eFigure 2A, E, and I in the Supplement).

To further assess the concordance between CSF biomarkers and visual PET assessment in terms of classification performance, we dichotomized CSF Aβ variables into abnormal (CSF Aβ-positive) and normal (CSF Aβ-negative) values based on the optimal cutoff points corresponding to the highest Youden J indices. The number of cases with discordant CSF Aβ status compared with visual PET assessments was higher for the newer assays (48 [18.3%] for modified Aβ42-INNITEST; 49 [18.7%] for Aβ42-EI; and 42 [16.0%] for Aβ42-MSD) than for the classic Aβ42-INNOTEST (31 [11.8%]) and consisted of mainly CSF Aβ42-positive and visual PET-negative cases (eTable 3 in the Supplement). However, the number of discordant cases for the newer assays (modified Aβ42-INNOTEST, Aβ42-EI, and Aβ42-MSD) was reduced significantly when using the Aβ42:Aβ40 or Aβ42:P-tau ratios (eTable 3 in the Supplement). As shown in Figure 3, using cutoffs obtained from the 2 ratios (Aβ42:Aβ40 or Aβ42:P-tau) resulted in better separation of visual PET-positive and -negative cases than CSF Aβ42 levels alone, and the ratios mainly reduced the number of cases in the discordant group that were positive for CSF Aβ42 and negative for visual PET findings (eTable 3 in the Supplement). The results were similar for CSF biomarkers measured using antibody-independent mass spectrometry–based RMP and quantitative PET assessment (eResults and eFigure 3 in the Supplement).

Spiking of CSF Samples With Aβ40

Addition of recombinant Aβ1-40 peptide to CSF samples caused a spike level–dependent decrease in measured CSF Aβ42 concentrations by as much as 62% when measured using the classic INNOTEST assay (eFigure 4A and D in the Supplement). In contrast, no differences in Aβ42 concentrations were observed when the samples were analyzed using the newer modified INNOTEST procedure (eFigure 4B and E in the Supplement) and MSD assay (eFigure 4C and F in the Supplement).

Discussion

In this study, we showed that the new modified Aβ42-INNOTEST, Aβ42-FL, Aβ42-EI, and Aβ42-MSD assays correlated better with Aβ42 values obtained with antibody-independent mass spectrometry–based RMP compared with the classic Aβ42-INNOTEST assay. The classic Aβ42-INNOTEST instead correlated better with the Aβ42:Aβ40 ratio obtained with mass spectrometry–based RMP compared with the other Aβ42 assays, a phenomenon that might be explained by the fact that the signal in the classic Aβ42-INNOTEST assay is somewhat quenched by Aβ40 levels. Of interest, the classic Aβ42-INNOTEST assay had a higher accuracy to predict visual PET assessment outcome compared with the newer modified Aβ42-INNOTEST, Aβ42-FL, Aβ42-EI, and Aβ42-MSD immunoassays. However, the CSF Aβ42:Aβ40 ratios from these assays performed better than the corresponding Aβ42 levels alone and had comparable performance to the classic Aβ42-INNOTEST level. The accuracy of the classic Aβ42-INNOTEST assay did not improve by using the Aβ42:Aβ40 ratio. For all the Aβ42 assays, the addition of T-tau and P-tau to Aβ42:Aβ40 did not improve the ability to predict cortical Aβ accumulation compared with the Aβ42:Aβ40 ratios alone.

The INNOTEST ELISA is one of the most extensively used assays for assessment of Aβ42 levels in CSF. However, this assay is limited by the matrix interference that may lead to inaccurate estimates of Aβ42 concentrations.12 The matrix effects are reduced in the newer assays (modified INNOTEST, FL, EI, and MSD), which are based on the analysis of diluted CSF samples.13-15 Accordingly, we found that CSF concentrations of Aβ42 derived from antibody-independent mass spectrometry procedure matched better with the data from the newer assays than the classic INNOTEST assay.

Visual rating is the only approved procedure for assessment of amyloid PET scans in the clinic and when selecting AD cases for clinical trials.1 Although quantitative approaches provide more informative data that might be critical for investigating longitudinal changes in amyloid burden and treatment effects, the concordance between visual and quantitative methods for establishing amyloid status is very high. Similar to previous studies,19,30 we found that only 25 cases (9.5%) were discordant according to visual and quantitative PET analysis with very good intermethod agreement (Cohen κ = 0.81). Most discordant cases were found in individuals who had been classified as amyloid negative by the visual analysis but as amyloid positive by SUVR analysis, demonstrating that visual analysis is more conservative than SUVR analysis; this finding is consistent with those of previous studies.19

Cerebrospinal fluid Aβ42 is a biomarker of amyloid deposition that is often used interchangeably or in combination with PET imaging in the diagnostic workup in the clinic or in clinical trials.1 The agreement between CSF Aβ42 and quantitative amyloid PET data has ranged from 80% to 90%,6-8 and this agreement might be improved by using the Aβ42:Aβ40 or Aβ42:tau ratios.9,10,31 However, for implementation of CSF AD biomarkers (Aβ42 level, Aβ42:Aβ40 ratio, and/or Aβ42:tau ratio) in routine clinical practice, establishing the concordance with the clinically approved visual amyloid PET ratings, and studying whether the concordance rate is affected by the choice of the immunoassay for CSF Aβ42 measurements are important. Herein, we showed that newer Aβ42-EI and Aβ42-MSD assays have similar performance with respect to association of visual read outcome and exhibit acceptable accuracy with visual [18F]flutemetamol PET status when using the Aβ42:Aβ40 ratio. With the classic INNOTEST assay, the AUC for Aβ42 alone was close to the Aβ42:Aβ40 ratios from the EI and MSD assays and did not increase any further when the classic INNOTEST Aβ42:Aβ40 ratio was used. The modification of the classic INNOTEST assay, which improved the correlation with mass spectrometry–based RMP Aβ42 values, resulted in decreased accuracy of Aβ42 levels alone but improved performance for the Aβ42:Aβ40 ratio, as was the case for other Aβ42 assays evaluated herein. These results could in part be explained by our spiking data, which suggested that Aβ42 concentrations obtained using the classic INNOTEST were influenced by Aβ1-40 and that in individuals with higher CSF levels of Aβ1-40, these effects might be more pronounced, resulting in a lower signal. Further analysis revealed that the CSF Aβ42:Aβ40 ratios from the newer immunoassays (modified INNOTEST, EI, and MSD) had a more pronounced bimodal distribution allowing improved separation of [18F]flutemetamol PET-positive and -negative populations compared with CSF Aβ42 levels alone. Moreover, compared with Aβ42 levels alone, the rate of decrease in sensitivity and specificity values around the cutoff points was less steep when using the Aβ42:Aβ40 ratios. However, we did not observe differences in the distributions and behavior of sensitivity and specificity values near cutoff between Aβ42 level and Aβ42:Aβ40 ratio for the classic INNOTEST assay. These results indicate that the Aβ42:Aβ40 ratio cutoffs for the new assays (modified INNOTEST, EI, and MSD) may be more reliable in terms of performance that is more robust with respect to small changes in cutoff values. In agreement with our findings, the CSF Aβ42:Aβ40 ratio has also been shown to provide a better prediction of prodromal AD compared with Aβ42 level alone when using the Aβ42-EI and Aβ42-MSD assays but not the classic Aβ42-INNOTEST or xMAP AlzBio3 (Fujirebio) assays.16,32

In the present study, the Aβ42:tau ratios were better predictors of visual [18F]flutemetamol PET classification than were Aβ42 levels alone. However, we did not observe improved accuracy when the Aβ42:Aβ40 ratios were combined with T-tau or P-tau compared with the Aβ42:Aβ40 ratios alone. Biochemical mechanisms underlying the better performance of the Aβ42:Aβ40 and Aβ42:tau ratios are not known. Interindividual variability in the production of CSF, the production and secretions of proteins by neurons such as Aβ and tau, and preanalytical factors may affect the accuracy of CSF Aβ42 levels in predicting amyloid status. Although all these effects could be partly compensated by using the ratios to Aβ40 or tau, at present, which of the mechanisms are mainly responsible for the better performance of the ratios and whether these mechanisms differ for ratios to Aβ40 or tau remain unclear. For example, some data suggest that CSF levels of tau are less affected by preanalytical factors than Aβ peptides.33-35 Consequently, variations in preanalytical handling should in theory be better compensated for by using Aβ42:Aβ40 ratios11 than Aβ42:tau ratios, suggesting that the Aβ42:Aβ40 ratios might be more useful in clinical practice as well as for tracking the emergence of amyloid deposition in longitudinal studies.

Limitations

One limitation that could have possibly influenced the result of the present study is that PET images were assessed by a single rater. However, this is unlikely considering that the findings were the same for quantitative measures (SUVR) of amyloid PET.

Conclusions

We showed that the newer Aβ42 assays (modified INNOTEST, EI, and MSD) correlated better with the antibody-free RMP than did the classic INNOTEST assay, possibly because the signal in the classic INNOTEST assay is partly quenched by Aβ1-40. However, the accuracy to correlate with visual [18F]flutemetamol PET status was decreased in the newer Aβ42 assays, a limitation that is overcome by using a Aβ42:Aβ40 or Aβ42:tau ratios. The CSF Aβ42:Aβ40 or Aβ42:tau ratios from the newer assays showed improved accuracy for detection of cortical Aβ fibrils as measured by PET. Moreover, the sensitivities and specificities of these newer assays were less influenced by moderate changes in the cutoffs when Aβ42:Aβ40 or Aβ42:tau ratios were used, a finding that is important when samples will be analyzed consecutively over time. The precision of the Aβ42:Aβ40 ratios in differentiating [18F]flutemetamol PET–positive and –negative visual reads did not improve further when combined with T-tau or P-tau values. Thus, our study provides a comprehensive overview of the correlation of the performance of CSF biomarkers across different immunoassays with amyloid PET status, which may influence the selection of immunoassays and biomarkers in future studies. Furthermore, our findings support implementation of the CSF Aβ42:Aβ40 and/or the Aβ42:tau ratios as biomarkers of amyloid deposition in clinical practice.

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Article Information

Corresponding Author: Shorena Janelidze, PhD, Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sölvegatan 19, BMC Building B11, 221 84 Lund, Sweden (shorena.janelidze@med.lu.se).

Accepted for Publication: July 24, 2017.

Published Online: November 6, 2017. doi:10.1001/jamaneurol.2017.2814

Open Access: This article is published under the JN-OA license and is free to read on the day of publication.

Author Contributions: Drs Janelidze and Hansson had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Mikulskis, Chiao, Blennow, Hansson.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Janelidze, Chiao, Hansson.

Critical revision of the manuscript for important intellectual content: Pannee, Mikulskis, Zetterberg, Blennow, Hansson.

Statistical analysis: Janelidze.

Obtained funding: Zetterberg, Blennow, Hansson.

Administrative, technical, or material support: Mikulskis, Chiao, Zetterberg, Hansson.

Study supervision: Hansson.

Conflict of Interest Disclosures: Drs Mikulskis and Chiao report employment by Biogen. Dr Zetterberg reports serving on advisory boards for Eli Lilly, Roche Diagnostics, and Pharmasum Therapeutics. Drs Zetterberg and Blennow report serving as cofounders of Brain Biomarker Solutions in Gothenburg AB, a GU Ventures–based platform company at the University of Gothenburg. Dr Blennow reports serving on advisory boards or as a consultant (unrelated to the work presented in the present study) for Eli Lilly and Company, Fujirebio Europe, IBL International, Novartis, and Roche Diagnostics. Dr Hansson reports serving on advisory boards or as a consultant for Eli Lilly and Company and receiving research support from Roche, GE Healthcare, and AVID Radiopharmaceuticals. No other disclosures were reported.

Funding/Support: This study was supported by the European Research Council, the Swedish Research Council, the Swedish Alzheimer Foundation, the Swedish Brain Foundation, the Marianne and Marcus Wallenberg Foundation, and the Swedish Federal Government under the ALF Agreement. Doses of [18]F-flutemetamol injection were sponsored by GE Healthcare. EUROIMMUN Aβ42, Aβ40, and T-tau kits were provided by EUROIMMUN. Analysis of cerebrospinal fluid samples using INNOTEST and Lumipulse kits were performed at Fujirebio Europe.

Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: The authors thank the study participants and the research nurses involved in the study for their invaluable contributions.

References
1.
Blennow  K, Mattsson  N, Schöll  M, Hansson  O, Zetterberg  H.  Amyloid biomarkers in Alzheimer’s disease.  Trends Pharmacol Sci. 2015;36(5):297-309.PubMedGoogle ScholarCrossref
2.
Ikonomovic  MD, Klunk  WE, Abrahamson  EE,  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):1630-1645.PubMedGoogle ScholarCrossref
3.
Strozyk  D, Blennow  K, White  LR, Launer  LJ.  CSF Aβ 42 levels correlate with amyloid-neuropathology in a population-based autopsy study.  Neurology. 2003;60(4):652-656.PubMedGoogle ScholarCrossref
4.
Tapiola  T, Alafuzoff  I, Herukka  SK,  et al.  Cerebrospinal fluid β-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain.  Arch Neurol. 2009;66(3):382-389.PubMedGoogle ScholarCrossref
5.
Wolk  DA, Grachev  ID, Buckley  C,  et al.  Association between in vivo fluorine 18-labeled flutemetamol amyloid positron emission tomography imaging and in vivo cerebral cortical histopathology.  Arch Neurol. 2011;68(11):1398-1403.PubMedGoogle ScholarCrossref
6.
Landau  SM, Lu  M, Joshi  AD,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Comparing positron emission tomography imaging and cerebrospinal fluid measurements of β-amyloid.  Ann Neurol. 2013;74(6):826-836.PubMedGoogle ScholarCrossref
7.
Mattsson  N, Insel  PS, Donohue  M,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Independent information from cerebrospinal fluid amyloid-β and florbetapir imaging in Alzheimer’s disease.  Brain. 2015;138(pt 3):772-783.PubMedGoogle ScholarCrossref
8.
Palmqvist  S, Zetterberg  H, Blennow  K,  et al.  Accuracy of brain amyloid detection in clinical practice using cerebrospinal fluid β-amyloid 42: a cross-validation study against amyloid positron emission tomography.  JAMA Neurol. 2014;71(10):1282-1289.PubMedGoogle ScholarCrossref
9.
Janelidze  S, Zetterberg  H, Mattsson  N,  et al; Swedish BioFINDER study group.  CSF Aβ42:Aβ40 and Aβ42:Aβ38 ratios: better diagnostic markers of Alzheimer disease.  Ann Clin Transl Neurol. 2016;3(3):154-165.PubMedGoogle ScholarCrossref
10.
Leuzy  A, Chiotis  K, Hasselbalch  SG,  et al.  Pittsburgh compound B imaging and cerebrospinal fluid amyloid-β in a multicentre European memory clinic study.  Brain. 2016;139(Pt 9):2540-2553.PubMedGoogle ScholarCrossref
11.
Vanderstichele  HM, Janelidze  S, Demeyer  L,  et al.  Optimized standard operating procedures for the analysis of cerebrospinal fluid Aβ42 and the ratios of Aβ isoforms using low protein binding tubes.  J Alzheimers Dis. 2016;53(3):1121-1132.PubMedGoogle ScholarCrossref
12.
Cullen  VC, Fredenburg  RA, Evans  C, Conliffe  PR, Solomon  ME.  Development and advanced validation of an optimized method for the quantitation of Aβ42 in human cerebrospinal fluid.  AAPS J. 2012;14(3):510-518.PubMedGoogle ScholarCrossref
13.
Bittner  T, Zetterberg  H, Teunissen  CE,  et al.  Technical performance of a novel, fully automated electrochemiluminescence immunoassay for the quantitation of β-amyloid (1-42) in human cerebrospinal fluid.  Alzheimers Dement. 2016;12(5):517-526.PubMedGoogle ScholarCrossref
14.
Pan  C, Korff  A, Galasko  D,  et al.  Diagnostic values of cerebrospinal fluid T-tau and Aβ42 using Meso Scale Discovery assays for Alzheimer’s disease.  J Alzheimers Dis. 2015;45(3):709-719.PubMedGoogle Scholar
15.
Vandijck  M, Moonen  R, Andreasson  U,  et al.  Correlation of the modified innotest β-amyloid 1-42 with a lc-ms:ms candidate reference method.  Alzheimers Dement. 2015;11(7)(suppl):385.PubMedGoogle ScholarCrossref
16.
Palmqvist  S, Zetterberg  H, Mattsson  N,  et al; Alzheimer’s Disease Neuroimaging Initiative; Swedish BioFINDER Study Group.  Detailed comparison of amyloid PET and CSF biomarkers for identifying early Alzheimer disease.  Neurology. 2015;85(14):1240-1249.PubMedGoogle ScholarCrossref
17.
Andreasen  N, Hesse  C, Davidsson  P,  et al.  Cerebrospinal fluid β-amyloid(1-42) in Alzheimer disease: differences between early- and late-onset Alzheimer disease and stability during the course of disease.  Arch Neurol. 1999;56(6):673-680.PubMedGoogle ScholarCrossref
18.
Clark  CM, Pontecorvo  MJ, Beach  TG,  et al; AV-45-A16 Study Group.  Cerebral PET with florbetapir compared with neuropathology at autopsy for detection of neuritic amyloid-β plaques: a prospective cohort study.  Lancet Neurol. 2012;11(8):669-678.PubMedGoogle ScholarCrossref
19.
Schreiber  S, Landau  SM, Fero  A, Schreiber  F, Jagust  WJ; Alzheimer’s Disease Neuroimaging Initiative.  Comparison of visual and quantitative florbetapir F 18 positron emission tomography analysis in predicting mild cognitive impairment outcomes.  JAMA Neurol. 2015;72(10):1183-1190.PubMedGoogle ScholarCrossref
20.
Leinenbach  A, Pannee  J, Dülffer  T,  et al; IFCC Scientific Division Working Group on CSF proteins.  Mass spectrometry–based candidate reference measurement procedure for quantification of amyloid-β in cerebrospinal fluid.  Clin Chem. 2014;60(7):987-994.PubMedGoogle ScholarCrossref
21.
Blennow  K, Hampel  H, Weiner  M, Zetterberg  H.  Cerebrospinal fluid and plasma biomarkers in Alzheimer disease.  Nat Rev Neurol. 2010;6(3):131-144.PubMedGoogle ScholarCrossref
22.
Pannee  J, Portelius  E, Minthon  L,  et al.  Reference measurement procedure for CSF amyloid β (Aβ)1-42 and the CSF Aβ1-42:Aβ1-40 ratio: a cross-validation study against amyloid PET.  J Neurochem. 2016;139(4):651-658.PubMedGoogle ScholarCrossref
23.
A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2014. http://www.R-project.org. Accessed September 17, 2016.
24.
Meng  XL, Rosenthal  R, Rubin  DB.  Comparing correlated correlation-coefficients.  Psychol Bull. 1992;111(1):172-175.Google ScholarCrossref
25.
Robin  X, Turck  N, Hainard  A,  et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves.  BMC Bioinformatics. 2011;12:77.PubMedGoogle ScholarCrossref
26.
Benaglia  T, Chauveau  D, Hunter  DR, Young  DS.  mixtools: an R package for analyzing finite mixture models.  J Stat Softw. 2009;32(6):1-29.Google ScholarCrossref
27.
Altman  DG.  Practical Statistics for Medical Research. London, England: Chapman & Hall:CRC; 1999.
28.
Buchhave  P, Minthon  L, Zetterberg  H, Wallin  AK, Blennow  K, Hansson  O.  Cerebrospinal fluid levels of β-amyloid 1-42, but not of tau, are fully changed already 5 to 10 years before the onset of Alzheimer dementia.  Arch Gen Psychiatry. 2012;69(1):98-106.PubMedGoogle ScholarCrossref
29.
De Meyer  G, Shapiro  F, Vanderstichele  H,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Diagnosis-independent Alzheimer disease biomarker signature in cognitively normal elderly people.  Arch Neurol. 2010;67(8):949-956.PubMedGoogle ScholarCrossref
30.
Zwan  MD, Ossenkoppele  R, Tolboom  N,  et al.  Comparison of simplified parametric methods for visual interpretation of 11C-Pittsburgh compound-B PET images.  J Nucl Med. 2014;55(8):1305-1307.PubMedGoogle ScholarCrossref
31.
Wang  MJ, Yi  S, Han  JY,  et al.  Analysis of cerebrospinal fluid and [11C]PIB PET biomarkers for Alzheimer’s disease with updated protocols.  J Alzheimers Dis. 2016;52(4):1403-1413.PubMedGoogle ScholarCrossref
32.
Hertze  J, Minthon  L, Zetterberg  H, Vanmechelen  E, Blennow  K, Hansson  O.  Evaluation of CSF biomarkers as predictors of Alzheimer’s disease: a clinical follow-up study of 4.7 years.  J Alzheimers Dis. 2010;21(4):1119-1128.PubMedGoogle ScholarCrossref
33.
Le Bastard  N, De Deyn  PP, Engelborghs  S.  Importance and impact of preanalytical variables on Alzheimer disease biomarker concentrations in cerebrospinal fluid.  Clin Chem. 2015;61(5):734-743.PubMedGoogle ScholarCrossref
34.
Toombs  J, Paterson  RW, Lunn  MP,  et al.  Identification of an important potential confound in CSF AD studies: aliquot volume.  Clin Chem Lab Med. 2013;51(12):2311-2317.PubMedGoogle ScholarCrossref
35.
Toombs  J, Paterson  RW, Nicholas  JM, Petzold  A, Schott  JM, Zetterberg  H.  The impact of Tween 20 on repeatability of amyloid β and tau measurements in cerebrospinal fluid.  Clin Chem Lab Med. 2015;53(12):e329-e332.PubMedGoogle ScholarCrossref
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