tranSMART Community Meeting 5-7 Nov 13 - Session 3: tranSMART and the One Mind for Research Data Exchange Portal Jeff Grethe, One Mind for Research One Mind for Research (http://1mind4research.org) is an independent, non-partisan, nonprofit organization dedicated to curing the diseases of the brain and eliminating the stigma and discrimination associated with mental illness and brain injuries. tranSMART will be a core application within the One Mind Brain Data Exchange Portal, scheduled to launch publicly in 2014. Traumatic Brain Injury (TBI) affects an estimated 10 million people worldwide, and tranSMART is one of the core applications within the portal used by researchers who are looking to improve diagnostics and discover more effective treatments for patients suffering from CNS- and TBI-related diseases.

1. www.1mind4research.org

2. THE WAY FORWARD……….
An Open-Science Framework
• Generate and Share Data:
– Use a portal system to access global coherent datasets
– Build an inter-operable infrastructure for collation, curation and hosting of
datasets for the R&D community
– Common standards and methods for the collection of the world’s largest
biomarker repositories for brain disorders
• Generate and Share Tools:
– Collectively develop next-generation animal models, imaging tools, stem cell
lines, biosensors, and more…
• Generate and Share Models:
– Apply advanced clinical informatics, computational biology and visualization
tools to create dynamic interactive Disease Maps and inform Clinical
Decisions Support and Practice Guidelines
• Create Insight:
– Tap Global Expertise (multi-disciplinary & global) – crowd-sourced solutions

3. THE CHALLENGE

4. DATA SHARING IS POORLY INCENTIVIZED

5. DATA AND TOOL SHARING IS NOT
SIMPLE ENOUGH
???

6. DATA SETS ARE BALKANIZED AND HARD
TO FIND

7. THE APOLLO PROGRAM

8. PORTAL ARCHITECTURE
Engagement Tools
• Facebook-like Activity Stream
• LinkedIn-like social networking
• Patient Engagement platforms
Analytics Marketplace
• Access to the world’s most advance Big Data Analytics Tools
• API allows both Open-Source and Proprietary Software to Plug-In
 Links Data – Experts - Analysis
Data Hub
• OS Infrastructure for Comprehensive Data Management
• Tiered Resource Ingestion Pipeline, DataSpace, Object
Models, Search, Web Services, Encyclopedias, Ontologies
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9. CASE STUDY

10. tranSMART CASE STUDY: TRACK-TBI
Prepared for ONE MIND
Sirimon O’Charoen, PhD
Manager, Translational Medicine
sirimon.ocharoen@thomsonreuters.com

11. Traumatic Brain Injury Numbers
• ~1.7 Million Reported TBI’s in US / Year
–
–
–
–
~52,000 Deaths ---------------------------------~275,000 Severe TBIs (sTBIs) ------------~1.37 M Mild TBIs (mTBIs)-----------?? M Unreported TBIs ---------------
3.4M
• ~ 360,000 servicemen/veterans with war-related TBI
• BUT: TBIs can happen to anyone:
– ~3.8 million sports related TBIs/yr in US (3.6 M unreported)
– ~300,000 vehicular TBI’s / yr in US (17% of TBIs)
– 35.2% of reported TBIs from falls
• TBI is a contributing factor to a third (30.5%) of all injuryrelated deaths in the United States.
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12. The Goal: Establishing the Natural History of
the TBI Spectrum
Accelerate the
understanding, both
clinically and
mechanistically, of the
natural course of TBI
Develop a new
classification of
TBI
Identify
predictive
measures of
outcomes
Develop new
diagnostic tools
Identify new
targets for
therapeutic
intervention
In order to:
Develop new treatments, preventions and cures and
move the discoveries into clinical practice for
improved patient outcomes
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13. TRACK-TBI MULTICENTER INITIATIVE
• Transforming Research and Clinical
Knowledge in Traumatic Brain Injury
(TRACK-TBI) Pilot
– Multicenter Implementation of the Common Data
Elements for Traumatic Brain Injury
• Aims
– Test and validate Traumatic Brain Injury Common
Data Elements (TBI-CDEs)
– Collect neuroimaging, proteomic, and genetic
biomarkers, clinical and outcome data

14. TRACK-TBI DATA
• Approximately 650
patients
• Mostly mild TBI
• Principle Investigators
– UCSF, San Francisco
General Hospital
• Geoffrey Manley, MD, PhD
– University of Pittsburgh
Medical Center
• David Okonkwo, MD, PhD
– University Medical Center
Brackenridge
• Alex Valadka, MD
– Mount Sinai Rehabilitation
Center
• Wayne Gordon, PhD
Yue JK, et al., J Neurotrauma, 2013 Jul 2.

15. TRACK-TBI DATA IN tranSMART
Goal: Curate/upload TRACK-TBI Data for data sharing and analysis at researcher’s fingertip
TRACK-TBI Data
QuesGen Database
SPSS
Collaborators
Curation Process
CDEs Mapping
Data QC
ETL
Delivery in tranSMART
Ready for analysis
-Exploratory analysis (tranSMART features)
-Advanced workflow (tranSMART features)
- Custom analysis (database access or R-plugin)
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16. tranSMART USER INTERFACE
•Data navigation: folder-structure
•Analysis: drag & drop
•Trainings were provided for all collaborators
•Same curated dataset can be accessed
without compressing and emailing files

17. ANALYSIS EXAMPLES
• 2 Publications focus on
– Follow-up prediction
– GFAP-BDP as a diagnostic biomarker
• How do analyses in tranSMART confirm the
published results?
• How quickly we can generate new hypotheses and
perform exploratory analyses in tranSMART?
– Data can be across domains (i.e. genotype/biomarker vs.
outcome, medical history vs. follow-up)

18. FOLLOW-UP PREDICTION
• Outcome follow-up is challenging*
– 3-month GOS-E: 77%
– 6-month GOS-E: 69%
• Rate of successful follow-up significantly depends*
– Years of Education
– History of Developmental Disorders
– Toxicology Lab Results at ED
– Homelessness
* Result from

19. LIVE DEMO
FOLLOW-UP PREDICTION
Lost-to-follow up
(6-month)
Years of Education
History of Developmental Disorders
Successful follow up
(69% at 6-month)

20. GFAP-BDP DIAGNOSTIC MARKER
• Glial fibrillary acidic protein (GFAP)
– Acute plasma level
– Optimal cutoff 0.68 ng/ml*
• Discriminate*
– CT intracranial lesion result
– Outcomes
• Other protein biomarkers may improve prediction
* Result from

21. GFAP-BDP DIAGNOSTIC MARKER:
CT RESULT
Publication Figure 1
Subset1: CT negative
Subset2: CT positive

22. GFAP-BDP DIAGNOSTIC MARKER:
OUTCOME GOS-E
Publication Figure 5

23. GFAP-BDP DIAGNOSTIC MARKER:
OPTIMAL CUTOFF
Subset1: GFAP<0.68 ng/ml
Subset2: GFAP≥0.68 ng/ml

24. ACCOMPLISHMENTS
Pilot
Evaluation
• tranSMART
implementation
• TRACK-TBI
Pilot curation
and upload
• User trainings
(>25 users)
• Feedbacks
• Validation of
publication
results in
seconds
On-going
• Data access for
collaborators
• New data
analysis
• Part of One
Mind Portal