ADNI Biomarker Core Leslie M Shaw John Q Trojanowski ICAD, Honolulu July 10, 2010 • • • • • • • • • • • ADNI Biomarker Core Established and maintained ADNI Biofluid Bank at UPenn, 24/7 Established reproducible CSF Ab42, t-tau, ptau181 immunoassays using Luminex xMAP/Innogenetics system; interlab study involved 7 ISAB and academic laboratories Developed AD – like biomarker signature/cutpoints using CSFs from ADNI-independent autopsy-based AD cases & agematched controls and determined incidence in ADNI cohorts (Ann Neurol, 2009) Detected abnormal Ab42 CSF concentration in 34% of cognitively normal subjects Assessments of longitudinal changes underway, an ADNI extension study Determined predictive performance of individual and combined CSF biomarkers for MCI → AD progression Further validation of the AD biomarker signature: – DeMeyer et al diagnosis-independent “mixture modeling” approach (Arch Neurol, 2010) – Significantly > 1 yr rate of hippocampal atrophy and LV volume in subjects with baseline Ab42 below cutpoint – Okonkwo et al characterized the relationship between CSF biomarker abnormalities and rate of decline in everyday function across the AD spectrum (Arch Neurol, 2010) Continue collaborative studies of data integration including imaging and biochemical biomarkers and neuropsychological tests (eg, Vemuri et al, Neurol, 2009; Landau et al, Neurol, 2010; Davitskos et al, NBoA, 2010; Nettiksimmons et al, NBoA, 2010) Developed and qualified an HPLC/MS-MS method for isoprostanes in CSF, BASELINE CSF data uploaded on ADNI website; completed plasma homocysteine data through year 2; CSF HCy BASELINE measured at Merck, uploaded Working closely with Kai Blennow on the International CSF QC program (sponsored by Alz Assn) to further promote the standardization of pre-analytical and analytical steps involved in CSF biomarker measurements. Plasma biomarker initiatives: – Plasma Ab42/40 interlab study, using Luminex/Innogenetics reagents, data analyses: involving 12 ISAB & academic labs, completed and posted on ADNI web site; ADNI longitudinal sample analyses initiated during 2010 – ISAB-sponsored studies of qualified RBM panels underway for 1066 ADNI BL & yr1 plasma in 2010 CSF sample collection for ADNI: •After overnight fast •Collect into polypropylene tube •Transfer to polypropylene transfer tube •No centrifugation •Freeze at site, thaw & aliquot at UPenn, storage at -80 0C Number of biofluids collected as of 6/30/2010 13,122 Number of aliquots in biofluid bank 126,681 CSF through year 4 Plasma through year 4 N 948 2621 Average time (mins) 35.11 67.94 95% CI (mins) 32.46-37.78 66.32-69.57 ADNI CSF Biochemical Biomarker Interlaboratory Study (All Data Are on ADNI Website) Participating Centers & Investigators University of Pennsylvania: Leslie M Shaw, John Trojanowski, Virginia M-Y Lee, Margaret Knapik-Czajka Innogenetics: Hugo Vanderstichele Sahlgrenska University Hospital: Kaj Blennow Friedrich-Alexander-Universitat Erlangen-Nurnberg: Jens Wiltfang, Piotr Lewczuk Pfizer Global Research & Development: Holly Soares, Nancy Raha Eli Lilly & Company: Robert A Dean, Eric Siemers, Richard Lachno, Brent Salfen, (Linco) Merck Research Laboratories: Adam Simon, William Potter Reproducibility of xMAP Immunoassay (Innogenetics reagents/Luminex) in the ADNI biomarker core lab Avg test/re-test %CV: Ab42, 5.7% t-tau, 5.6% p-tau181, 11.5% CSF Biomarker Cutpoints Established Using CSFs Collected from ADNIIndependent Autopsy-Based AD and Age-Matched Cognitively Normal Subjects Tau Ab1-42 p-Tau181p Tau/Ab1-42 0.913 0.753 0.917 0.856 0.938 192 ng/mL 23 ng/mL 0.39 0.10 0.22 p-tau181p/Ab1-42 LR TAA ROC AUC 0.831 Threshold values 93 ng/mL Sensitivity (%) 69.6 6.4 67.9 85.7 91.1 100 Specificity (%) 92.3 76.9 73.1 84.6 71.2 76.9 Test accuracy (%) 80.6 87.0 73.1 85.2 81.5 88.9 Positive predictive value (%) 90.7 81.8 67.9 85.7 77.3 82.4 Negative predictive value (%) 73.8 95.2 70.4 84.6 88.1 100 UPenn Autopsy-Based CSF Biomarker AD Signature in the ADNI Study Cohorts % of ADNI patients in whom biomarker signature was detected using ROC cutpoints AD MCI NC Ab1-42 91 78 34 Tau/Ab1-42 ratio 89 69 34 LRTAA model 89 70 31 Ab1-42 & p-tau181 abnormal 82 64 21 Ab1-42 abn but p-tau181 norm 9 10 17 Ab1-42 norm but p-tau181 abn 5 6 15 Ab1-42 & p-tau181 normal 4 20 47 LRTAA = a logistic regression model that includes Tau, Ab42, and ApoE e4 allele number; ROC = receiver operating characteristic curve Survival analyses for ADNI MCI subjects: progression to AD for BASELINE CSF biomarkers > or < cutpoints Ab42<192 pg/mL t-tau/Ab42>0.39 As of June 28, 2010 riskTAA2>0.34 Autopsy-based CSF biomarker AD signature in ADNI MCI→AD progressors N MCI→AD MCI→MCI original MCI 82 109 191 Ab1-42 (<192 pg/mL) 90.2% 64.2% 75.4% t-tau (>93 pg/mL) 58.5% 35.8% 45.5% p-tau181 (>23 pg/mL) 85.4% 59.6% 70.7% t-tau/Ab1-42 (>0.39) 92.7% 56.9% 70.7% p-tau181/Ab1-42 (>0.1) 92.7% 67.0% 78.0% riskTAA2 89.0% 58.7% 71.7% (>0.22) Frequency distribution plots for Ab1-42 ADNI data as of 6/30/2010 Further validation of the AD biomarker signature • DeMeyer, et al, diagnosis-independent analysis of ADNI CSF biomarker data: correctly • • classified as AD 94% of autopsy-proven cases of AD in pre-mortem CSF (Arch Neurol, 67:1-8, 2010): – 91% of ADNI AD subjects had the AD CSF signature – Confirmed the AD signature more than 1/3rd of the elderly cognitively normal control We showed that there was a significantly greater rate of hippocampal atrophy and lateral ventricular volume expansion in subjects with baseline Ab42 below the cutpoint Okonkwo, et al, showed that CSF abnormalities are associated with functional decline (FAQ) in NC and MCI subjects but do not predict functional decline in AD. Persons with t-tau and Ab42 abnormalities are at greatest risk of functional impairment (Arch Neurol 67:688-696, 2010). ADNI Data Integration is off and Running MRI and CSF biomarkers in normal, MCI, and AD subjects Diagnostic discrimination and cognitive correlations Temporal Ordering of Biomarkers of AD Reflects Disease Progression Predictive performance of biomarkers is time dependent with Ab42 the earliest index of disease pathology and tau a later index. This time course of biomarker pathology provides a useful framework for interpretation of biochemical and imaging biomarker data. Shaw, et al., 2007; Jack, et al., 2010; Trojanowski, et al, 2010 Plasma Ab42/40 interlaboratory qualification study GROUP CENTER INVESTIGATOR Pharmaceutical Merck Mary Savage Pfizer Holly Soares, now with BMS Eli Lilly Robert Dean University Clinic, Erlangen Piotr Lewczuk Radboud University, Nijmegen Mariel Verbeek University Hospital, Amsterdam Rien Blankenstein Washington University, St Louis David Holtzman Molndal University, Goteborg Kaj Blennow Lille, France Luc Buee Mayo Clinic, Jacksonville Steve Younkin University of Penn, Philadelphia Leslie Shaw Academic Diagnostic company Innogenetics, Ghent Poster presentation at ICAD 2010 Hugo Vanderstichele ADNI 2 Biomarker Core Update on the Recently Completed Interlab Study of Plasma Aß Measures in Non-ADNI Pooled Plasma Samples • • • • • Statistical analyses of the 12 center interlaboratory "round-robin" study report for the INNO-BIA plasma Aß forms immunoassay(Innogenetics, Belgium) showed: Total reproducibility across these 12 centers (combined within-center and between-center %CV) was less than 16.7% for Aß42 and Aß40 and within individual centers the overall reproducibility is even better. The ADNI Biomarker Core laboratory which is funded by ADNI 1 and GO to measure plasma Aß42 and Aß40, achieved total analytical error (combined within- and between-day %CVs) ranging from 0.9 to 4.9% for plasma Aß42, 1.2 to 6.6% for Aß40 and up to 7.6% for the ratio of Aß42/Aß40. Thus the ADNI Biomarker core has initiated measurement of plasma Aß42 and Aß40 concentrations in longitudinal samples of ADNI subjects, using this analytically qualified methodology, to determine the changes in these biomarkers over time and determine their value as indices of progression from MCI to AD. 110 INNO-BIA plasma Aß forms immunoassay kits have already been provided as an in-kind contribution to ADNI study by INNOGENETICS. This will help to significantly resolve controversies surrounding the significance of measuring plasma Aß as an MCI/AD biomarker. ADNI GO and ADNI 2 • • • • • • Receive, bank and monitor 24/7 CSF, plasma and serum samples from ADNI GO and ADNI 2 subjects Apply qualified Ab42, t-tau and p-tau181 to all ADNI GO and ADNI 2 subjects at baseline Extend to earlier timepoint in the MCI to AD progression biomarker assessments Plasma Ab42 data on serial plasma samples from ADNI subjects will be generated, analyzed Apply Rules Based Medicine panel results from ADNI 1 for plasma and CSF Continue collaboration on the integration of imaging and biochemical biomarker data in a variety of statistical models Efforts underway to improve standardization • ADNI • Alz Assn International qc program • UPenn/Wash U collaboration underway on • • ELISA/xMAP relationships UPenn/BIOCARD collaboration with Marilyn Alberts Innogenetics-sponsored but investigator-led workgroup on standardization guidelines It takes a great team effort! John Q Trojanowski Uwe Christians Kaj Blennow Virginia M-Y Lee Supported by the NIH/NIA and families Holly Soares Chris Clark of our patients Adam Simon Steve Arnold Robert Dean Hugo Vanderstichele Eric Siemers Magdalena Korecka Piotr Lewczuk Margaret Knapik-Czajka William Potter Magdalena Brylska ADNI investigators include (complete listing available at Teresa Waligorska www.loni.ucla.edu\ADNI\Coll Michal Figurski aboration\ADNI_Manuscript_ Ravi Patel Citations.pdf). Leona Fields