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Leslie M Shaw and John Q Trojanowski
Standardization of measurement methods for AD biomarkers in biofluids:
  • Analyses of CSF for A?1-42, t-tau and p-tau181 moved from the Research-Use-Only Fujirebio AlzBio3 xMAP bead-based immunoassay to the fully automated Roche Elecsys® platform following extensive validation studies (Bittner, 2016; Shaw, 2016) and for A?42, comparisons with validated reference method LC/MSMS using the primary reference standard preparation of A?42, provided by the Institute for Reference Materials and Measurements (IRMM) following finalization of replicate amino acid analyses(Korecka, 2014; Shaw, 2016; Kuhlman, 2017).  This transition to the fully automated Elecsys® platform supports an important aim for the ADNI Biomarker Core in the ADNI3 grant renewal namely to support the implementation of AD biomarkers in future clinical trials making use of a highly validated methodology with robust, reproducible cross-laboratory performance standardization that will enable effective implementation of universal cut-point values (Hansson, 2018; Schindler, 2018).  Starting with the CSF samples collected from ADNI3 participants A?1-40 will be added to A?1-42, t-tau and p-tau181 in order to provide measurement of the A?1-42/A?1-40 ratio in each ADNI3 CSF sample.  In addition, the Biomarker core provided Roche Elecsys-based A?1-42, A?1-40, t-tau and p-tau181 measurements in all DIAN participant CSF samples as part of a collaborative study between DIAN and ADNI.  A subset of ADNIGO/2 CSF samples were also analyzed as part of this study and results are summarized in a Methods report posted April, 2018.
  • Implementation of a fully validated reference LC/MSMS method for CSF A?42 and further validated for CSF A?40 and A?38 (see Korecka, 2014, Panee, 2016; Kuhlman, 2016) for measurements in all ADNIGO/2 BASELINE and LONGITUDINAL CSF samples over a total of 70 analytical runs. The Methods document and dataset for these analyses were uploaded to the LONI ADNI website, June, 2018.  The methods document includes frequency plots for each analyte and for the A?42/A?40 ratio and makes use of cut-points based on ROC analysis wherein FBP PET served as the AD biomarker, and documents major analytical factors including precision performance and experience and included one change in the lot of calibration standards (Korecka, 2018).
  • Important NOTE: The preparation of Certified Reference Material for CSF A?1-42 was completed late 2017 (Kuhlmann, 2017, Certification report). A number of immunoassay vendors are collaborating pre-competitively on the use of this material for adjusting their calibrators based on the three prepared human CSF pools whose A?1-42 concentrations were established by participating reference laboratories each using validated LC/MSMS methods including two JCTLM-listed reference methods (Korecka, 2014; Leinenbach, 2014).  The purpose of this effort is to achieve harmonization across the different immunoassay platforms.  In concert with this effort the ADNI Biomarker Core laboratory will make use of the three CRMs to adjust all ADNI GO/2 CSFs that were measured by a reference UPLC/MSMS method (Korecka, 2014) and we plan to collaborate with Roche on adjustment of all ADNI CSF A?1-42 values based on the CRMs and this will assure that ADNI CSF A?1-42 data are based on this common CRM-based standardization process.
  • Recently a number of studies (Lewczuk,2017; Janeldze S, 2016; 2017; Niemantsverdriet, 2017) have reported that compared to CSF A?1-42 alone, the CSF A?1-42/A?1-40 ratio might improve:
  1. The prediction accuracy of Alzheimer’s disease (AD) in MCI study participants
  2. Discrimination of AD from other forms of dementia
  3. Concordance between CSF and PET amyloidosis

The statistical analyses of this ADNI dataset as reported in the Methods document focused on confirming the improved detection of amyloid pathology when using the CSF A?1-42/A?1-40 ratio vs CSF A?1-42 alone based on improved concordance between the A?1-42/A?1-40 ratio and FBP amyloid PET compared to CSF A?1-42 alone.  A secondary focus of the statistical analyses was assessment of the diagnostic utility of A?1-42/A?1-38 ratio.  An improved concordance from 83% to 89% was observed for the A?1-42/A?1-40 ratio as described in the Methods document.  Similar degree of improvement was observed for the A?1-42/A?1-38 ratio.  Further studies are required to determine the potential added value of A?1-38.

Given the heightened interest in and growing number of studies showing the improved utility of the A?1-42/A?1-40 ratio, an effort is planned to prepare CRMs for A?1-40 analogous to what was done for A?1-42 and we will participate in this effort as well.  In the ADNI3 phase we are adding A?1-40 to A?1-42, t-tau and p-tau181 measurements using the Roche Elecsys® platform in CSFs collected in ADNI3.

Pre-analytical factors:
  • Another key element of overall standardization of CSF AD biomarker measurements is recognition and control of pre-analytical factors including (1) timing of CSF sampling; (2) location of sampling and volume of CSF; (3) type of puncture needle; (4) collection method (gravity drip or syringe pull); (5) blood contamination; (6) type of plastic CSF comes into contact with; (7) the number of transfer steps; (8) additives; (9) shaking/mixing; (10) heat; (11) centrifugation; (12) storage temperature; (13) the # of freeze/thaw cycles; (14) storage time at -80 0 These factors were considered in a recent review and recommendations for future study were made including a proposed collaborative study that includes a unified CSF collection protocol (Hansson, 2018).  Many investigators have contributed to these studies of pre-analytical factors and all are acknowledged in Hansson, 2018 and will not be tabulated here due to the need for conservation of space.  In the ADNI study the recommended time for LP, (as well as blood draws for serum and plasma collections), is in the morning following an overnight fast; for LPs, based on improved patient safety, the use of a blunt tipped atraumatic Sprotte needle is recommended-22 g and gravity drip, although 24 g Sprotte and syringe pull without use of plastic catheter tubing is permitted and favored by a number of experienced ADNI clinical sites.  Since tube transfer has been shown to reduce CSF A?1-42 concentration, keeping this to a minimum in the preparation of aliquots is recommended.  In the ADNI study this factor is reduced to a minimum for both gravity drip and syringe pull as described in the ADNI3 Biomarker Sample Collection, Processing and Shipmenten documnet .When CSF aliquots are prepared in the Biomarker core laboratory, an additional transfer step is undertaken in order to permit mixing of the two tubes of CSF and eliminate any possible gradient effects.   All ADNI CSF samples undergo one thaw-freeze cycle in the preparation of 0.5 mL aliquots in the Biomarker core laboratory, thus one additional freeze-thaw cycle.  Available study data suggests that up to 2 freeze-thaw cycles will not result in diminished CSF A?1-42 concentration (Lewczuk, 2017). Further description of the time dynamics for CSF is available in the “BIOFLUID BANKING” section.
  • There is increased interest in the development and validation of plasma-based biomarkers for at least as a screening test to detect AD pathology. Recent studies show promise that new approaches to measurements of A?1-42 and A?1-40 can detect AD with AUC values approaching 0.9 (Ovod, 2017; Nakamura, 2018) when amyloid PET is used as the standard of comparison, whereas in the past results across 26 studies using then-available immunoassays were not consistent for reliable detection of AD (Rissman, 2012).  New and improved mass spectrometry based methods (Ovod, 2017; Nakamura, 2018) and immunoassays (Song, 2018) are now being further evaluated with the promise that one or more of these will prove to be rugged and reliable for use as screening tests in the context of treatment trials as well as in the clinic.  Essential to progress in development of rugged and reliable AD biomarkers in plasma is recognition and control of pre-analytical factors that affect the concentration measurements.
  • A proposed set of guidelines for the standardization of pre-analytic variables was recently published (O’Bryant et al, 2015). A review of plasma and serum processing experience in the ADNI study is available in the “Biofluid Banking” section.
  • With the acceleration of studies and assessments of various platforms and biomarker analytes a key need is for determinations and definitions for best practice pre-analytical procedures including sample processing time and temperature, number of freeze-thaw cycles, plastic tube type, volume of sample aliquot in relationship to tube volume, sample stability at different temperatures, the need to check for and identification of other factors such as the presence of HAMA(human anti-mouse antibodies) that are well known to cause interference in various immunoassays in routine laboratory testing(Sturgeon, 2018), and hemoglobin.
  • A recently published study (Keshavan, 2018) described the effect of repeated freeze-thaw cycles on plasma A?1-42, A?1-40, t-tau and serum NFL using the Quanterix high sensitivity platform. Up to four freeze-thaw cycles did not influence concentrations of these biomarkers to a significant degree with at most minor reductions in A?40 after the 4th The authors recommended that for measurements that include A?40 be limited to no more than 2 freeze-thaw cycles.  In our view this study suggests that careful documentation of the effect of freeze-thaw is needed for each analytical methodology as these investigators have done for the Simoa (Quanterix) platform.
  • Round robin studies will be an essential step for determination of the comparative utilities and robustness of these new biomarker tests and we look forward to participation in these.
  • The Alzheimer’s Association Global Biomarkers Standardization Consortium (GBSC) is actively considering addition of blood based biomarkers to the CSF QC program that is being run by Kaj Blennow and colleagues in Gothenburg Sweden.

Bittner T, Zetterberg H, Teunissen CE, Ostlund RE, Jr., Militello M, Andreasson U et al (2016) Technical performance of a novel, fully automated electrochemiluminescence immunoassay for the quantitation of beta-amyloid (1-42) in human cerebrospinal fluid. Alzheimers Dement 12:517–526.  PMID: 26555316

Shaw LM, Fields L, Korecka M, Waligorksa T, Trojanowski JQ, Allegranza D, et al. Method comparison of A?(1-42) measured in human cerebrospinal fluid samples by liquid chromatography-tandem mass spectrometry, the INNO-BIA AlzBio3 assay, and the Elecsys® ?-Amyloid(1-42) assay. Alzheimers Dement 2016;12:668.

Korecka M, Waligorska T, Figurski M, Toledo JB, Arnold SE, Grossman M, Trojanowski JQ, Shaw LM. Qualification of a surrogate matrix-based absolute quantification method for amyloid-??? in human cerebrospinal fluid using 2D UPLC-tandem mass spectrometry. Journal of Alzheimer’s disease: JAD. 2014;41(2):441-51. PMID: 24625802. {C12RMP1}

Korecka M, Figurski M, Fields L, Trojanowski JQ, Shaw LM.  2D-UPLC tandem mass spectrometry measurement of A?1-42, A?1-40 and A?1-38 in ADNI2 and ADNIGO CSF.  ADNI Methods document, 6/20/2018.

Leinenbach A, Pannee J, Dulffer T, Huber A, Bittner T, Andreasson U, Gobom J, Zetterberg H, Kobold U, Portelius E, Blennow K. Mass spectrometry-based candidate reference measurement procedure for quantification of amyloid-beta in cerebrospinal fluid. Clin Chem. 2014; 60:987–994. PMID: 24842955. {C11RMP9}

Kuhlmann J, Boulo S, Andreasson U, Bierke M, Pannee J, Charoud-Got J, et al.  The certification of Amyloid ?1-42 in CSF ERM®-DA481/IFCC and ERM®-DA482/IFCC. 2018 Reference Materials Report, JRC 107381.

Kuhlmann J, Andreasson U, Pannee J, Bjerke M, Portelius E, etal.  CSF A?1-42-an excellent but complicated Alzheimer’s biomarker-a route to standardization.  Clin Chim Acta 2017; 467: 27-33.

Hansson O, Seibyl J, Stomrud E, Zetterberg H, Trojanowski JQ, Bittner T, Lifke V, Corradini V, Eichenlaub U, Batrla R, Buck K, Zink K, Rabe C, Blennow K, Shaw LM.  CSF biomarkers of Alzheimer’s disease concord with amyloid-beta PET and predict clinical progression: a study of fully automated immunoassays in BioFINDER and ADNI cohorts. Alzheimers Dement. 2018; https://doi.org/10.1016/j.jalz.2018.01.010 [Epub ahead of print].

Schindler SE, Gray JD, Gordon BA, Xiong C, Bartrla-Uttermann, Quan M, Wahl S, Benzinger TLS, Holtzman DM, Morris JC, Fagan AM.  Cerebrospinal fluid biomarkers measured by Elecsys assays compared to amyloid imaging.  Alzheimers Dement. 2018; in press, https://doi.org/10.1016/j.jalz.2018.01.013

Hansson O, Mikulskis A, Fagan AE, Teunissen C, Zetterberg H, Vanderstichele H, Molinuevo JL, Shaw LM, Vandijck M, Berbeek MM, Savage M, Mattsson N, Lewczuk P, Batrla R, Rutz S, Dean RA, Blennow K.  The impact of preanalytical variables on measureing CSF biomarkers for Alzheimer’s disease diagnosis: a review.  Alzheimer’s Dementia 2018, in press, https://doi.org/10.1016/j.alz.2018.05.008.

Lewczuk P, Matzen A, Blennow K, Parnetti L, Molinuevo JL, Eusebi P, Kornhuber J, Morris JC, Fagan AM. Cerebrospinal fluid Ab42/40 corresponds better than Ab42 to amyloid PET in Alzheimer’s disease. J AlzheimersDis 2017;55:813-822. PMID: 27792012

Janeldze S, Pannee J, Mikulskis A, Chiao P, Zetterberg H, Blennow K, Hansson O. Concordance between different amyloid immunoassays and visual amyloid positron emission tomographic assessment. JAMA Neurol 2017;74:1492-1501. PMID: 29114726

Janeldze S, Zetterberg H, Mattsson N, Palmqvist S, Vanderstichele H, Lindberg O, van Westen D, Stomrud E, Minthon L, Blennow K, for the Swedish BioFINDER study group and Hansson O.  CSF A?42/A?40 and A?42/A?38 ratios: better diagnostic markers of Alzheimer’s disease.  Ann Clin Transl Neurol 2016; 3: 154-165.  PMID: 27042676

Niemantsverdriet E, Ottoy J, Somers C, De Roeck E, Struyfs H, Soetewey F, Verhaeghe J, Van den Bossche T, Van Mossevelde S, Goeman J, De Deyn PP, Mariën P, Versijpt J, Sleegers K, Van Broeckhoven C, Wyffels L, Albert A, Ceyssens S, Stroobants S, Staelens S, Bjerke M, Engelborghs S. The Cerebrospinal Fluid A?1-42/A?1-40 Ratio Improves Concordance with Amyloid-PET for Diagnosing Alzheimer’s Disease in a Clinical Setting. J Alzheimers Dis. 2017;60:561-576.  PMID: 28869470

Lewczuk P, Riederer P, O’Bryant SE, Verbeek MM, Dubois B, Visser PJ, etal.  Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: an update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry.  The World J of Biol Psych 2017; http://dx.doi.org/10.1080/15622975.2017.1375556

Ovod V, Ramsey KN, Mawuenyega KG, Bollinger JG, Hicks T, Schneider T, etal.  Amyloid ?concentrations and stable isotope labeling kinetics of human plasma specific to central nervous system amyloidosis.  Alzheimer’s Dement 2017; 13: 841-849.  PMCID:PMC5567785

Nakamura A, Kaneko N, Villemagne VL, Kato T, Doecke J, Dore V, et al.  High performance plasma amyloid-? biomarkers for Alzheimer’s disease.  Letter. Nature;  http://www.nature.com/doifinder/10.1038/nature25456.

Song L, Lachno DR, Hanlon D, Shepra D, Shepiro A, Jeromin A, Gemani D, Talbot JA, Racke MM, Dage JL, Dean RA.  A digital enzyme-linked immunosorbent assay for ultrasensitive measurement of amyloid-? 1-42 peptide in human plasma with utility for studies of Alzheimer’s disease therapeutics.  Alz Res Ther 2018; 58:soi 10.1186/s 13195-016-0225-7.

Sturgeon C. Tumor Markers, Chapter 31, in: Tietz Textbook of Clinical Chemistry and Molecular Diagnostics, 6th Edition; Rafai N, Horvath AN, Wittwer CT, eds. Elsevier, St Louis, MO, pp 436-478,

Keshavan A, Helsegrave A, Zetterberg H, Schott JM.  Stability of blood-based biomarkers of Alzheimer’s diseae over multiple freeze-thaw cycles.  Alz Dementia: Diag Assessment Dis Monit 2018; in press, https://doi.org/10.1016/j.dadm.2018.06.001