FP6

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FP6
Molecular Phenotyping to Accelerate Genomic
Epidemiology
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Concept of MolPAGE
GENOMIC EPIDEMIOLOGY
measurement, manipulation and analysis of
omics scale data in thousands of subjects
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MolPAGE Consortium

• European Consortium
• 11 Universities/Research Institutes
• 2 Pharma
• 5 Biotech/SME
• 4 Year programme (Oct 04-08)
• 12 million Euro

Coordinated by the University of Oxford
Professor John Bell
Professor Mark McCarthy
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Programme Goals
The application of genomic, metabonomic and
proteomic tools to develop novel technical, data
analysis and integration protocols that will
enable disease biomarker typing and discovery
projects on an epidemiological scale
The identification and validation of biomarkers
for use as pre-clinical predictors of metabolic
disease
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Programme Overview

• 1. The evaluation of sample collection and
  storage methodology
• to optimally reduce sample variation and maximise
  analyte stability

• 2. The development of genomic, metabonomic and
  proteomic tools
• to prepare for molecular phenotyping on an
  epidemiologic scale
• relevant to both biomarker discovery and
  subsequent biomarker measurement in large sample
  sets
• Includes proof of principle biomarker discovery
  (medium-scale)

• 3. The development of project specific tools to
  support data warehousing, data interrogation and
  statistical analysis
• integrated approaches to data analysis across
  multiple platforms
• integrated approach to data storage and
  dissemination

.with a clinical focus on diabetes and
cardiovascular disease
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Work Package Overview
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Some vignettes

• Standardization
• Assessing variability in omics measures
• Medium scale biomarker discovery
• Application to large cohorts
• Data management

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1. Standardisation

• Contribute to efforts to standardise sample
  collection strategies for genomic
  epidemiology future-proofing biobank
  collections for future analysis. Build on UK
  Biobank efforts in this respect.
• Contribute to efforts to generate standards and
  norms for genomic epidemiology
• study design and analysis
• sample collection, processing and storage
• measurement of exposure and clinical
  phenotypes
• data formats, management, manipulation and
  storage
• analyte measurement (-omics scale)
• ethics, data privacy, material transfer
• meta-data
• To ensure that in 5 years from now, it will be
  much easier to work across multiple
• European biobanks than currently.

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2. Sources of variation in omics data

• UK TWIN STUDY
• Twin volunteers recruited through media campaigns
• Healthy adult population 18
• Representative of UK pop
• 500 MZ and 1,500 DZ pairs seen clinically in
  detail
• Body comp DEXA fat total and central, fasting
  glucose,insulin,leptins, lipids
• gt10000 twins on database with questionnaire data
• All will have fresh DNA fasting blood by 2007

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Decomposing variance
MZ female Representative for BMI
DZ female Representative for BMI
Technical
Variance
Biological
40 pairs
20 pairs
Genetic
MZ
DZ
Me-DNA RNA Proteome Peptidome Metabonome
MZ
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Power studies
Lon Cardon, Krina Zondervan Oxford (WP9)
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3. Biomarker discovery
discordant MZ twins
plasma serum urine subcutaneous fat omental
fat muscle
healthy individuals stratified for future disease
disk
proteomics
Metabonomics LC-MS NMR
legacy samplesfrom prospective cohorts
peptidomics
samples gathered at surgery
epigenomics
new samplesfrom prospective cohorts
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Twins discordant for BMI
Plasma
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Peptide display
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Peptide display heat map
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Putative biomarker
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4. Evaluation of biomarkers
Need for high throughput methods based on
affinity reagents
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Large scale Ab generation
http//www.proteinatlas.org/
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Serum array performance
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Insulin Pancreas
http//www.proteinatlas.org/
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Thyroglobulin precusor Thyroid
http//www.proteinatlas.org/
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Data Warehouse
Repository
Gene Peptides
Raw/ data files
METABONOMICS
NovoNordisk ICL
NMR LCMS
Measurement types
Assay
Proteomics
TRANSCRIPTOMICS
BioVisioN
Peptides (Sequence)
NovoNordisk OGT
Proteins (UNIPROT)
Roche
Protein Arrays
KTH
DNA Methylation SNP
TRANSCRIPTOMICS
Epigenomics, CNG
NovoNordisk OGT
DNA methylation SNP
Epigenomics, CNG
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WP11 - Training

• 1) Annual training courses
• Statistical genetics training (Pavia, 4-8th
  July 2005)
• Transcriptomics workshop (Pavia, 20-24th
  March 2006)
• Data reduction techniques in metabonomics
  proteomics (2007)
• 2) Mobility awards
• Competitive awards to support inter-partner
  training visits
• 3) Science Workshops (technology/analysis)
• Data Warehousing workshop (September 2006)
• Proteomics workshop (March 2007)

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Dissemination Activities

• 1) Project events open to wider scientific
  community
• Training courses in Pavia
• Public Technology Workshop (Paris May 8-10th
  2005)
• Follow up Technology Workshop (autumn 2008)

• 2) Contribution to standards
• Standard setting workshop (October 2006)
• Publication of SOPs

• 3) Publicity
• Project overview presentations, Press release,
  case studies etc..
• Project web pages (www.molpage.org)

• 4) Interaction with other projects
• EU projects e.g. MolTOOLS, GenomeEUtwin,
  GA2LEN
• SystemsX consortium interaction

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Thomas Bergman
Peter Schulz -Knappe
Ed Southern Spiros Servos
Mark Lathrop Ivo Gut
Stephan Hoffmann
Kurt Berlin Florian Eckhardt
Mathius Uhlen
Dominique Langin
Fredrik Ponten
Tim Spector
Vladimir Stich
Juris Viksna
Luisa Bernardinelli
Alvis Brazma Ugis Sarkans
Jeremy Nicholson
Hanno Langen Everson Nogoceke
Esper Boel Jan Fleckner
Commission Project Officer Dr. Shahid Baig
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Summary

• MolPAGE developing approaches to enable large
  scale genomic epidemiology
• Contributing to standardisation
• methods development
• informatics, and
  analysis
• Medium-scale biomarker discovery
• Long term application to existing/future
  European biobanking initiatives