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The Unknown Unknown of Biorepositories: Overcoming Obstacles Benjamin M. Greenberg, MD, MHS Director, Transverse Myelitis and Neuromyelitis Optica Program.

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Presentation on theme: "The Unknown Unknown of Biorepositories: Overcoming Obstacles Benjamin M. Greenberg, MD, MHS Director, Transverse Myelitis and Neuromyelitis Optica Program."— Presentation transcript:

1 The Unknown Unknown of Biorepositories: Overcoming Obstacles Benjamin M. Greenberg, MD, MHS Director, Transverse Myelitis and Neuromyelitis Optica Program University of Texas Southwestern Medical Center

2 Potential Roles of a Biorepository Understand biology of a disease Understand response to therapy Create diagnostic technologies Identify prognostic biomarkers Identify new conditions

3 Multiple Sclerosis Throughout History 1868 – Jean-Martin Charcot describes in detail, clinical multiple sclerosis and relates it to white matter lesions.

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5 Eugene Devic, What devic described was a monophasic illness of bilateral ON and myelitis in quick succession. He saw one case, but his fellow Fernand Gault ( ), reviewed sixteen cases, some had relapses and published in 1894

6 Neuromyelitis Optica Revisited In 1999, Wingerchuk, et. al., reviewed 71 cases from the Mayo clinic and defined NMO as a relapsing disorder with longitudinally extensive transverse myelitis (LETM) and normal brain MRI That turns out to be inaccurate

7 How Should We Define Diseases? Clinically – Non-specific lumping of various syndromic phenotypes into one heterogenous category Pathologically – Ignores potential phenotypic variation – Multiple biologic pathways result in same pathology Molecularly – Limited markers available – Incomplete understanding of biology

8 The NMO Battlefield: Biology and Semantics Is NMO a spectrum of Multiple Sclerosis? Patients don’t seem to respond to MS therapy 40% died within 5 years of respiratory failure Preferential effect on spinal cord and optic nerves When brain is involved, unique patterns can be seen Can have unusual CSF patterns compared to MS Yet, some patients can have clinical and radiographic patterns that initially look like MS

9 Incomplete NMO Definitions Optic neuritis and partial spinal lesions, were usually not NMO, but rather MS even with normal brain MRI. – If you used ON, TM and normal brain scan would be wrong 50% of the time. So more specific criteria (LETM) was important for distinguishing MS from NMO

10 NMO IgG Arrives Announced at 2004 AAN Lennon et al lancet Antibody binds to pia and virchow robin spaces, distribution suggested of antigen in perivascular region. Claudia Lucchinetti identified pathology around blood vessels

11 The Alchemy of Biorepositories: Turning Samples into Gold A sample’s value is based on several factors – When was the sample obtained – How was the sample obtained – How was the sample processed – How was the sample stored – What prospective data is subsequently gathered about the patient.

12 Example Patient Patient is Born Patient has exposures Patient has various illnesses Patient has first symptom Patient is Diagnosed Patient is Treated Patient has Outcome

13 The Ideal Biorepository Patient is Born Patient has exposures Patient has various illnesses Patient has first symptom Patient is Diagnosed Patient is Treated Patient has Outcome

14 Reality Patient is Diagnosed Patient is Treated Patient has Outcome

15 There are Two Kinds of Biorepositories Patient is Born Patient has exposures Patient has various illnesses Patient has first symptom Patient is Diagnosed Patient is Treated Patient has Outcome

16 The Classic Approach to Disease Specific Biorepositories Cancer – Patient suspected of cancer based on symptoms or tests. – Tissue acquired and banked Genetic Conditions – Patient diagnosed and DNA acquired Rare Non-Cancer/Non-Genetic Diseases – The repository is research lab specific Genetics research labs acquire DNA Infectious Disease labs draw serum Nutrition labs draw whole blood

17 The Donald Rumsfield Analysis of Biorepositories

18 “ Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns, there are things we know we know. We also know there are known unknowns, that is to say, we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know.” -Donald Rumsfeld, Frmr. Secretary of Defense February 12, 2002

19 Translation: We Don’t Know The Questions That Are Going to Be Asked Tomorrow Everything can’t be designed around hypothesis driven research

20 Remodeling Repositories Most diseases are the result of the following formula: Disease = Genetics + Environment + Timing

21 Examples of Discoveries Since 2000 siRNA miRNA Granulebacter bethesdensis in patients with CGD Metapneumovirus in children with hospitalizations for respiratory infections. Th17 immune cells – 3 articles in 2003 – Over 700 in 2009

22 The Broken Repository Model The silo approach has failed – Every institution has their own program. Hypothesis driven research is the only way to get funding Academia is not inherently collaborative Intellectual Property issues create obstacles.

23 Increased Challenges For Rare Disease Repositories Too few numbers Too few points of entry into study Too little infrastructure for longitudinal expenses. Solution: Combining repositories with registries and partnering up with common conditions………

24 Finding Common Ground Much can be learned by studying outliers. – Comparing related, albeit distinct diseases allows for new discovery – Neuromyelitis Optica versus Multiple Sclerosis versus Myasthenia Gravis The notion of “controls” – Allows for collaborations between “common” and “rare” disease groups.

25 Collaborative Solutions

26 Status 10 enrolling sites Over 1700 cases – 1393 MS – 110 NMO – 141 TM 500 controls *Overrepresentation of the rare diseases!!!!

27 Broad Sample Type Acquisition Whole Blood PaxGene Tubes Serum Plasma Cells

28 Removing The Silo Approach to Research The ACP repository model not only collects broad amounts of samples and matched clinical data – Samples provided to researchers without IP/publication restrictions – Samples provided to researchers on the condition that data generated in research is returned to the repository.

29 Third Party Biorepositories Advance Discovery EBV Researcher Recruits Patients EBV serologies are Determined Results Published Vitamin D Researcher Recruits Patients Vitamin D Levels are Determined Results Published Genetic Researcher Recruits Patients HLA type is Determined Results Published

30 Third Party Biorepositories Advance Discovery Central Repository of Patients EBV Titers Determined Vitamin D Levels Determined Cross tabulation of results HLA Type Determined

31 Conclusions The Unknown Unknowns require broad sample and data set acquisitions Rare diseases need to link with common ones Third party repository stewards are required to breakdown the barriers of complex research Public policy: every visit is a research visit………


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