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 A  42, t-tau, ptau 181 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 & age- matched controls and determined incidence in ADNI cohorts (Ann Neurol, 2009) Detected abnormal A  42 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 A  42 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 A  42/40 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 through year 4Plasma through year 4 N Average time (mins) % CI (mins) 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 C Number of biofluids collected as of 6/30/ ,122 Number of aliquots in biofluid bank 126,681

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: A  42, 5.7% t-tau, 5.6% p-tau 181, 11.5%

Tau A  1-42 p-Tau 181p Tau/A  1-42 p-tau 181p /A  1-42 LR TAA ROC AUC Threshold values 93 ng/mL192 ng/mL23 ng/mL Sensitivity (%) Specificity (%) Test accuracy (%) Positive predictive value (%) Negative predictive value (%) CSF Biomarker Cutpoints Established Using CSFs Collected from ADNI- Independent Autopsy-Based AD and Age-Matched Cognitively Normal Subjects

% of ADNI patients in whom biomarker signature was detected using ROC cutpoints ADMCINC A  Tau/A  1-42 ratio LR TAA model A  1-42 & p-tau 181 abnormal A  1-42 abn but p-tau 181 norm A  1-42 norm but p-tau 181 abn 5615 A  1-42 & p-tau 181 normal UPenn Autopsy-Based CSF Biomarker AD Signature in the ADNI Study Cohorts LR TAA = a logistic regression model that includes Tau, A  42, and ApoE e 4 allele number; ROC = receiver operating characteristic curve

Survival analyses for ADNI MCI subjects: progression to AD for BASELINE CSF biomarkers > or < cutpoints A  42 <192 pg/mLt-tau/A  42 >0.39 riskTAA2>0.34 As of June 28, 2010

Autopsy-based CSF biomarker AD signature in ADNI MCI→AD progressors MCI→ADMCI→MCIoriginal MCI N A  1-42 (<192 pg/mL) 90.2%64.2%75.4% t-tau (>93 pg/mL)58.5%35.8%45.5% p-tau 181 (>23 pg/mL)85.4%59.6%70.7% t-tau/A  1-42 (>0.39) 92.7%56.9%70.7% p-tau 181 /A  1-42 (>0.1) 92.7%67.0%78.0% riskTAA2 (>0.22)89.0%58.7%71.7% Frequency distribution plots for A  1-42 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 1/3 rd 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 A  42 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 A  42 abnormalities are at greatest risk of functional impairment (Arch Neurol 67: , 2010).

Temporal Ordering of Biomarkers of AD Reflects Disease Progression Shaw, et al., 2007; Jack, et al., 2010; Trojanowski, et al, 2010 Predictive performance of biomarkers is time dependent with A  42 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.

GROUPCENTERINVESTIGATOR Pharmaceutical Merck Mary Savage Pfizer Holly Soares, now with BMS Eli Lilly Robert Dean Academic 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 Diagnostic company Innogenetics, Ghent Hugo Vanderstichele Plasma A  42/40 interlaboratory qualification study Poster presentation at ICAD 2010

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 A  42, t-tau and p-tau 181 to all ADNI GO and ADNI 2 subjects at baseline Extend to earlier timepoint in the MCI to AD progression biomarker assessments Plasma A  42 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 Virginia M-Y Lee Chris Clark Steve Arnold Hugo Vanderstichele Magdalena Korecka Margaret Knapik-Czajka Magdalena Brylska Teresa Waligorska Michal Figurski Ravi Patel Leona Fields Uwe Christians Kaj Blennow Holly Soares Adam Simon Robert Dean Eric Siemers Piotr Lewczuk William Potter ADNI investigators include (complete listing available at aboration\ADNI_Manuscript_ Citations.pdf). Supported by the NIH/NIA and families of our patients