CSF Biomarkers: Perspective from Industry and Public ... · CSF Biomarkers: Perspective from...

CSF Biomarkers: Perspective

from Industry and Public/Private

Partnerships

William Z Potter, MD, PhD

Co-Chair Emeritus, FNIH BC Neuroscience

Steering Committee & Sr Advisor, OD, NIMH

RASAD, Melbourne, March 28, 2012

Biomarkers: The Essential Link

• Symptom Based Diagnoses of Brain Diseases – A Black Box

– Biomarkers are now accepted as a research tool for staging a disease process

– Quantitative issues come to the fore in multisite studies recruiting over time and using values to select patients (batch issue)

• Testing Hypotheses of Drug Action

– Biomarkers essential to demonstrate action of drug in CNS, the more precise the better

Biomarkers for Hypothesis Testing

• Definition for Drug Development:

– Biomarker = Any Measure of a Drug Action Proximal to a Clinical Effect

• Biochemical (PET, MRS & CSF* for CNS drugs)

• Physiological – EEG, FDG PET, fMRI, ASL, etc

• Behavioural (Responses to Tasks)

• Definition for CNS Disease State

– Biomarker = Quantifiable Measure in Brain Tissue* (including CSF) associated with Severity or Course of Clinical Symptoms

* Plasma and Urine can be Utilized when Established to Reflect CNS

What % of Mechanisms Tested?

Adis R & D Database: Compound Classes

that have at least Entered Phase I

• >75 Potential Antidepressant Targets

• 50 Antipsychotic Targets

• >150 Targets for Alzheimer’s Disease!!

– Only 8 have had associated Biomarker with

6/8 focused on Cognitive Symptoms

Potential & Known Targets for Alzheimer's Disease

• 3-beta hydroxysteroid dehydrogenase inhibitors

• Acetylcholine release stimulants

• Acetylcholinesterase inhibitors

• Adenosine A1 receptor modulators

• Adenosine A2 receptor modulators

• Adenosine triphosphatase stimulants

• Adenosylmethionine decarboxylase inhibitors

• Adenylate cyclase stimulants

• Adrenergic receptor agonists

• Advanced glycosylation end product inhibitors

• Alpha adrenergic receptor antagonists

– Alpha 1 adrenergic receptor antagonists

– Alpha 2 adrenergic receptor antagonists

• AMPA receptor agonists

• Amyloid inhibitors

– Amyloid beta-protein inhibitors

– Amyloid precursor protein secretase inhibitors

• Angiogenesis inhibitors

• Antioxidants

• Hypoxia-inducible factor-1 alpha inhibitors

• Apolipoprotein A I stimulants

• Apoptosis stimulants

• Benzodiazepine receptor inverse agonists

• Beta-secretase inhibitors

• Butyrylcholinesterase inhibitors

• Calcium channel agonists

• Cannabinoid receptor agonists

• Carnitine acetyltransferase stimulants

Source: Adis R&D Insights Database

Alzheimer's Disease (cont.)

• CB1 cannabinoid receptor antagonists

• CCR5 receptor antagonists

• Cdc2 kinase inhibitors

• Cell differentiation stimulants

• Cell membrane permeability enhancers

• Cell-replacements

• Central nervous system stimulants

• Chelating agents

• Chloride channel agonists

• Cholinergic receptor modulators

– Muscarinic receptor agonists

Muscarinic M1 receptor agonists

Muscarinic M4 receptor agonists

– Muscarinic receptor antagonists

Muscarinic M2 receptor antagonists

Muscarinic M3 receptor antagonists

• Cholinergic receptor modulators (cont.)

– Nicotinic receptor modulators

Alpha4-beta2-nicotinic-receptor-modulators

Alpha4 beta2 nicotinic receptor agonist

Alpha7 nicotinic acetylcholine receptor

modulators

Alpha7 nicotinic acetylcholine receptor

agonists

• Corticotropin-releasing hormone stimulants

• Cyclo-oxygenase 2 inhibitors

• Cytokine modulators

– Cytokine inhibitors

– Cytokine synthesis inhibitors

• DNA topoisomerase II inhibitors

• DNA-directed RNA polymerase stimulants



• Dopamine receptor agonists

– Dopamine D1 receptor agonists

– Dopamine D2 receptor agonists

• Dopamine D2 receptor antagonists

• Dopamine uptake inhibitors

• Estrogen receptor modulators

– Estrogen receptor agonists

– Estrogen receptor antagonists

• Fibroblast growth factor stimulants

• Free radical scavengers

• Nitric oxide synthase type II inhibitors

• G protein-coupled receptor modulators

• GABA modulators

– GABA A receptor agonists

GABA A alpha 2 receptor agonists

GABA A alpha 3 receptor agonists

– GABA B receptor antagonists

GABA-A receptor antagonists

• Gamma secretase modulators

– Gamma-secretase inhibitors

• Glial cell line-derived neurotrophic factor agonists

• Glucocorticoid receptor antagonists

• Glucose stimulants

• Glutamate agonists

• Glutamate receptor antagonists

• Glutamate release antagonists

• Glycine agonists

• Glycine NMDA-associated agonists

• Glycine reuptake inhibitors

• Glycogen synthase kinase 3 inhibitors

• Gonadotropin releasing hormone agonists

• Gonadotropin releasing hormone antagonists

• Growth hormone releasing factor agonists

• Histamine H3 receptor antagonists

• HMG-CoA reductase inhibitors



• Immunomodulators

• Immunophilin modulators

• Immunostimulants

• Immunosuppressants

• Insulin-like growth factor I agonists

• Intercellular signalling peptide and protein stimulants

• Interleukin 2 stimulants

• Lipid peroxidation inhibitors

• L-lactate dehydrogenase stimulants

• Melatonin MT1 receptor agonists

• Melatonin MT2 receptor agonists

• Membrane transport protein inhibitors

• Microtubule protein inhibitors

• Microtubule-associated protein modulators

• Mitochondrial protein stimulants

• Mitochondrial-permeability-transition-pore-modulators

• Mitogen-activated protein kinase inhibitors

• Mitosis inhibitors

• Mixed-lineage kinase inhibitors

• Monoamine oxidase inhibitors

– Monoamine oxidase B inhibitors

• Monoamine uptake inhibitors

• Nerve growth factor stimulants

• Neuropeptide stimulants

• Neurotransmitter modulators

– Neurotransmitter stimulants

• NF-kappa B inhibitors

• Nitric oxide donors

• Nitric oxide synthase type II inhibitors

• NMDA receptor agonists

• NMDA receptor antagonists

• Notch signalling pathway inhibitors

• Opioid receptor agonists

• Ornithine decarboxylase inhibitors



• Oxidoreductase stimulants

• Peptide stimulants

• Peroxisome proliferator-activated receptor agonists

– Peroxisome proliferator-activated receptor gamma

agonists

• Phospholipase A2 inhibitors

• Phosphoric diester hydrolase inhibitors

• Plasminogen activator inhibitor-1 antagonists

• Platelet activating factor inhibitors

• Platelet activating factor stimulants

• Platelet aggregation antagonists

• Potassium channel antagonists

• Progesterone receptor antagonists

• Prolyl endopeptidase inhibitors

• Prostaglandin endoperoxide synthase inhibitors

• Prostaglandin synthase inhibitors

• Protein synthesis stimulants

• Reactive oxygen species stimulants

• RNA synthesis inhibitors

• Selective estrogen receptor modulators

• Serotonin modulators

– Serotonin 1A receptor agonists

– Serotonin receptor antagonists

Serotonin 1A receptor antagonists

Serotonin 2 receptor antagonists

Serotonin 2A receptor antagonists




– Serotonin uptake inhibitors

• Sigma-1 receptor agonists

• Signal transduction pathway inhibitors

• Sodium channel antagonists

• Somatotropin receptor antagonists

• Spermidine/spermine N1-acetyltransferase stimulants



• STAT transcription factor inhibitors

• Survivin protein inhibitors

• Synuclein inhibitors

• Tau protein inhibitors

• Tubulin polymerisation promoters

• Testosterone congener stimulants

• Thromboxane A2 synthase inhibitors

• Thyrotropin releasing hormone agonists

• Transcription factor inhibitors

– Transcription factor AP-1 inhibitors

• Tubulin inhibitors

• Tumour necrosis factor inhibitors

• Tumour necrosis factor production inhibitors

• Type 4 cyclic nucleotide phosphodiesterase inhibitors

• Vesicular monoamine transporter 2 inhibitors

• Virus replication inhibitors


Lumbar Puncture

• Excellent Safety Record

• Acceptance for Alz Studies;

Required for ADNI 2

Collaborative

• Critical to Evaluate Drugs

Targeted to Abeta and Tau

• Go/No Go Decisions

possible in Volunteers for

Gamma Secretase and

BACE Inhibitors

Time (hr)

-24 -12 0 12 24 36 48 60 72

A40 (

pM

)

0

300

600

900

1200

Vehicle, n=8

L'988 0.3 mpk, n=6

L'988 1.0 mpk, n=6

L'988 3.0 mpk, n=6

L'988 10.0 mpk, n=4

Baseline samples taken at -20, -1 & 0 hr predosecrossover design** p<0.05 vs. Vehicle, 0.3 mpk & 1 mpk* p<0.05 vs. Vehicle & 0.3 mpkstatistics shown for 24 hr only

Validation of Conscious CMP Rhesus Monkey Model

-Secretase Inhibitor, L-000897988, Dose Response

PO Dose

**

**

*

GSI: CSF Sampling from Cisterna Magna Ported (CMP)

Conscious Rhesus Monkeys – 3 mg/kg = red plot

Time (hr)

-24 -12 0 12 24 36 48 60 72

A40 (

pM

)

0

300

600

900

1200

Vehicle, n=8

L'988 0.3 mpk, n=6

L'988 1.0 mpk, n=6

L'988 3.0 mpk, n=6

L'988 10.0 mpk, n=4

Baseline samples taken at -20, -1 & 0 hr predosecrossover design** p<0.05 vs. Vehicle, 0.3 mpk & 1 mpk* p<0.05 vs. Vehicle & 0.3 mpkstatistics shown for 24 hr only

Validation of Conscious CMP Rhesus Monkey Model

-Secretase Inhibitor, L-000897988, Dose Response

PO Dose

**

**

*

GSI: CSF Sampling from Cisterna Magna Ported (CMP)

Conscious Rhesus Monkeys & Limited Effects in HVs* at MFD*

Maximum Effect in HVs at MFD*

*HVs = Healthy Volunteers; MFD = Max Feasible Dose

No Go

Lessons Learned with CSF Abeta?

• The Lilly Secretase Inhibitor produced

<10% decrease in Abeta – might have

argued against taking it forward into patients

• Field now looking for safe BACE Inhibitors

that produce 75% Decreases –e.g. Merck

• Little evidence of clear effects with antibody

approaches – to be seen whether useful

clinical effects achieved without taking into

account whether relevant analytes in CSF

are consistently affected

Biomarkers of Disease State

• Industry Perspective on Issues Facing AD

Drug Development when Focus on

Slowing or Preventing

• Role of Private Partner Scientific Board

(PPSB), formerly Industry Scientific

Advisory Board (ISAB)

15

Original Industry Strategic

Advisory Board Goals: ADNI PROTEOMICS SUBTEAM

Taken from Holly D. Soares

March 30, 2009

Neuroscience Steering Committee Meeting

Proteomics

Metabonomics

AD Biomarkers Drug Development

• No Validated Biomarkers that Correlate with Cognitive

Decline (e.g. Disease Progression Markers).

– Could provide additional evidence supporting drug efficacy.

– Disease progression markers that change in response to treatment are

tools to monitor treatment response and compliance.

• No VALIDATED diagnostic test for AD

• Goal: Ideally Blood but CSF if Necessary

– Fluid biomarker performance to be compared to brain imaging

– Go beyond Pre-Specified ADNI Analytes (e.g. Abeta)

PPSB Summary of Biochemical Results

Alzheimer’s & Dementia 6 (2010) 230–238

Update on the biomarker core of the Alzheimer’s

Disease Neuroimaging Initiative subjects

John Q. Trojanowski,*, Hugo Vandeerstichele, Magdalena Korecka,

Christopher M. Clark, Paul S. Aisen, Ronald C. Petersen, Kaj

Blennow, Holly Soares, Adam Simon, Piotr Lewczuk, Robert

Dean, Eric Siemers, William Z. Potter, Michael W. Weiner,

Clifford R. Jack, Jr.,William Jagust, Arthur W. Toga, Virginia M.-Y.

Lee, Leslie M. Shaw; and the Alzheimer’sDisease Neuroimaging

Initiative

18

PPSB CSF A1-42 concentration distribution in

ADNI MCI subjects at BASELINE visit

40 60 80 100 120 140 160 180 200 220 240 260 280 3000

20

40

60

A1-42 concentration (pg/mL)

nu

mb

er

192 pg/mL*

*cutoff concentration from earlier patient with post-mortem confirmation study

Proteomics

Metabonomics

Plasma and CSF Studies

• Plasma: Targeted Multiplex Proteomic Strategies to Identify Biomarkers in Alzheimer’s Disease To qualify a multiplex immunoassay panel as a tool to diagnose and

monitor disease progression in the ADNI one-year plasma samples. - Approved Budget $430,500.00

• CSF: Targeted Multiplex Proteomic Strategies to Identify CSF-Based Biomarkrees in Alzheimer’s disease Specific Aim 1: To qualify a 151 analyte multiplex immunoassay panel

as a tool to diagnose and monitor disease progression in the ADNI cohort using baseline and one year cerebral spinal fluid (CSF).

Specific Aim 2: To examine BACE levels and enzymatic activity in CSF in the ADNI baseline and one year CSF samples.

Specific Aim 3: To qualify a 30 analyte mass spectroscopy MRM panel as a tool to diagnose and monitor disease progression in the ADNI cohort using baseline and one year CSF samples.

RBM CSF Peptide Findings

• Elevated FABP, PPP, Nt-BNP & VEGF in

AD vs HC - replicates previous reports

• Novel : Cancer 19-9 & CD40 Antigens

• Plasma/CSF Correlation Surprises: – 5 values from 0.89-0.64 - leptin, C-Reactive Protein,

apolipoprotein(a), immunoglobulin A, chemokine CC-4

and pancreatic polypeptide(PPP)

– Adjusted for age, gender and APOE status all of which

had large impact on many peptide values in CSF and

plasma

0.5 1 1.5

plasma value

1.5

2

2.5

csf

valu

e

0 1 2

plasma value

-1.5

-1

-0.5

csf

valu

e

-1.6 -1.4 -1.2

plasma value

-0.6

-0.4

-0.2

0

csf

valu

e

2 3

plasma value

1

1.5

2

csf

valu

e

Association Between Plasma and CSF Measurements

ADNI data from RBM

Interleukin-8 (IL-8) (pg/mL)Interleukin-8 (IL-8) (pg/mL) Leptin (ng/mL)Leptin (ng/mL)

Macrophage Colony-Stimulating Factor 1 ( (ng/mL)Macrophage Colony-Stimulating Factor 1 ( (ng/mL) Macrophage Inflammatory Protein-1 beta ( (pg/mL)Macrophage Inflammatory Protein-1 beta ( (pg/mL)

Analyte (unit)

Baseline Diagnosis:

AD

Control

MCI

Issues Emerging from RBM Data

• Core CSF analytes Informative but:

– Are values batch assay dependent even with

“standardized” kits?

– How much variation around cut-off points if

new batch run every day, week, month?

– Impact on any multivariate combos and

apparent association with disease state

• Are plasma/CSF correlations reproducible?

– Contribution of batch effect to correlations

Evolution of Translational Omics:

Lessons Learned and the Path Forward*

• “…Due to the increased risk of overfitting large data sets

in the development of the computational model, the need

for rigor, validation, and accountability is even higher

than for other single biomarker-based tests.”

• Premature applications included “the series of genomics-

based predictive tests used in clinical trials at Duke

University; the commercial tests OncotypeDx,

MammaPrint, Ova1, AlloMap Testing, CorusCAD and

the Tissue of Origin Test…”

• Formal recommendations have emerged

*Christine M. Micheel, Sharly J. Nass, and Gilbert S. Omenn, Editors; Committee on the

Review of Omics-Based Tests for Predicting Patient Outcomes in Clinical Trials; Board

on Health Care Services; Board on Health Sciences Policy; Institute of Medicine

25

Gaps and What’s Next?

• Scientific:

– Lack of biomarkers correlating with disease progression in AD

– Lack of robust biomarker distinctions between likely subtypes of AD

– Lack of knowledge on when any difference first detectable in ultimate

AD subject vs healthy control

• Methodologic:

– Robust standardized measures of single CSF analytes

– Role of multiplex approaches: what is reasonable number of analytes to

include in an assay to achieve same level of performance as with single

targeted measure?

– Will very specific peptide forms, only identifiable with mass spect,

prove crucially informative?

• What are Most Important Next Investments for CSF?

Integration of Efforts?

IRMM, IFCC, JPND, EMEA,

AIBL, J-ADNI…

Discovery & IVD

Companies

US ADNI, FNIH, FDA, CPI/CAMD

AA?

4/23/2012 Confidential Soares Draft 27

Members of Proteomic Work Groups

Holly Soares, - BMS

Peter Alfinito - BMS

Sophie Allauzen – Novartis

Neil Buckholtz - NIA

Patricia Cole – Eisai

Bob Dean - Lilly

Ashok Dongre – BMS

Mats Ferm – AstraZeneca

Dan Holder – Merck

Fred Immerman – Pfizer

David Shera – Merck Statistics

Walter Koroshetz – NINDS/NIH

Brad Navia – J&J

Max Kuhn – Pfizer Statistics

Eve Pickering – Pfizer Statistics

James McNulty – Nat. alliance Mental Illness

Susanne Ostrowitski – Roche

William Potter – FNIH

Jeff Seeburger – Merck

Les Shaw – UPenn

Eric Siemers – Lilly

John Trojanowski – UPenn

Marc Walton – FDA

Hong Wan - Wyeth

Tony Wyss-Coray – Stanford

Alison Drone – FNIH

Judy Siuciak – FNIH

Adam Simon – Independent Contributor

Panos Zagouras – Pfizer Systems Bio

Biomarkers in Brain Disease:

Challenges and Opportunities 3-5 February 2013 The Møller Centre, Cambridge, UK

Scientific organisers

Giovanni Frisoni IRCCS Fatebenefratelli, Italy

Andreas Jeromin Banyan Biomarkers, USA

Andy Lockhart GlaxoSmithKline, UK

William Potter formerly Merck, USA

Full details at: www.wellcome.ac.uk/conferences

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