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P3G: an international consortium in Human Genome Epidemiology

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Use the information to design new preventative and therapeutic strategies. Offer tailored preventive advice that is based on the knowledge of the genetic ... – PowerPoint PPT presentation

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Title: P3G: an international consortium in Human Genome Epidemiology


1
P3G an international consortium in Human Genome
Epidemiology

Ultimate GoalsFor the understanding of
gene-environment causes of chronic diseasesFor
better public health strategies
2
The Causal Complexity of Chronic Diseases
Diabetes Asthma Heart Disease Schizophrenia Cancer
Multiple Sclerosis Obesity Arthritis
Genetics
Diet Lifestyle
Environment
Social Structure
webs of causation
3
Why Study Gene-Environment Interactions?
  • Obtain a better estimate of the population
    attributable risk for genetic and environmental
    risk factors by accounting for their joint
    interactions
  • Strengthen the associations between
    environmental factors and diseases by examining
    these in genetically susceptible individuals
  • Help dissect disease mechanisms by focusing on
    biological pathways most relevant to that
    disease, and environmental factors most relevant
    to the pathway.
  • Determine which specific compounds in a complex
    mixture of chemicals (from pollution, diet, etc.)
    cause disease.
  • Use the information to design new preventative
    and therapeutic strategies
  • Offer tailored preventive advice that is based
    on the knowledge of the genetic profile of an
    individual.

Hunter, Nature Reviews/Genetics 2005
4
Resources needed for identifying genetic risk
factors and gene-environment interactions
affecting the predisposition to chronic diseases
Comprehensive knowledge of genetic
variation Genotyping Technologies Cohorts -
Phenotypes - Exposures - Large
Size Analytical Tools
5
Example of Sample Size Issue for detecting ONE
interaction for a dichotomous trait and a 10
exposure
Hunter, Nature Reviews/Genetics 2005
6
What 10,000 incident cases in a gene-environment
study can provide
  • (with power calculations that that take into
    account considerations of misclassification of
    exposure and outcome data, and realistic data
    collection scenarios)
  • For genotypic and environmental prevalences of
    10 and above, 10,000 cases will provide adequate
    power for interaction effects with an MDOR
    greater than 2.

(MDORs defined as the smallest odds ratio that
can be detected at p10-4 and power80).
Paul Burton, UK BioBank Technical Report 2005
7
What 10,000 incident cases in a gene-environment
study can provide
  • (with power calculations that that take into
    account considerations of misclassification of
    exposure and outcome data, and realistic data
    collection scenarios)
  • 2. For a genotypic prevalence as low as 1 there
    will be adequate power to detect substantial (OR
    between 2 and 3) direct genetic effects. For this
    low genotype prevalence, gene-environment
    interactions will only be detectable for very
    large interaction effects (e.g. OR gt 7).
  • 3. 10,000 cases will provide a powerful platform
    for genome-wide indirect association studies
    (requiring rigorous definition of statistical
    significance of plt10-7).

Paul Burton, UK BioBank Technical Report 2005
8
How long does it take to reach 10,000 cases in a
cohort with 500,000 cases?
Breast cancer (F) 17 yrs
Colorectal cancer 22 yrs
Prostate cancer (M) 22 yrs
Lung cancer 34 yrs
Stroke 18 yrs
MI and coronary death 8 yrs
Diabetes mellitus 6 yrs
COPD 13 yrs
Hip fracture 21 yrs
Alzheimers disease 18 yrs
Parkinsons disease 23 yrs
Paul Burton, UK BioBank Technical Report 2005
9
Public Population Project in Genomics
  • A consortium dedicated to fostering international
    collaboration between researchers and projects in
    the field of population genomics

10
P3G History and Launching Phase (2003-2005)
  • International meetings leading to the creation of
    P3G
  • 2003 London, Montreal, Manchester
  • 2004 Helsinki, Tallinn, Toronto
  • Supported by Wellcome Trust, European Union
  • Genome Canada and Genome Quebec
  • Non-for-profit organization incorporated in 2004
  • Secretariat and Observatory created February
    2005
  • Seed money from Genome Quebec and Genome Canada
    for the launching phase

11
P3G mandate
  • create a network in population genomics that will
    comprise over 3 million participants for
    epidemiological studies
  • provide statistical power for analysing complex
    genetic and environmental determinants of health
    and disease
  • leverage the combined expertise of hundreds of
    researchers around the world
  • promote communication among national and
    international organizations
  • increase the ability to share and generate new
    knowledge dedicated to improve public health and
    welfare.

12
P3G Consortium Model
An international resource for the coordination
and exchange of ideas and data that will be
generated by the various population biobanks
Kora-Gen
LifeGene (Sweden)
(Germany)
Generations
NHLBI
(Scotland)
(USA)
(Canada)
(Europe)
NIGM
Genoma Espana
(Mexico)
(Spain)
Danubian Biobank Foundation
CIGMR
WAGHP (Australia)
(UK)
(Europe)
ALSPAC
LifeLines
(UK)
(Netherlands)
13
P3G Membership
Regular Member Associate Member Individual Member
14
NEED FOR HARMONIZATION
Analogie Bill Ollier
15
HARMONIZATION IS NOT REGIMENTATION
16
P3G Operational Chart
P3G General Assembly
Funders Auditors
P3G Board of Directors
P3G Secretariat
P3G Steering Committee
IWG 1 (Social/Clinical/ Environmental)
IWG 2 Informatics
IWG 3 Ethics and Governance
IWG 4 Epidemiology/ Biostatistics
Core
Core
Core
Core
Core
Core
Core
Core
Core
Core
Core
Core
P3G OBSERVATORY
17
International Working Groups (IWGs), leaders and
early outcomes
Social, Environmental andBiochemical Investigations Leader H. Erich Wichmann (KORA-Gen, Germany) -Common Core Variables for Population Based Studies -Common DNA Quality and Quantity Control -Conceptual model for harmonization of physiologic and biochemical measures
Knowledge CurationAnd Information Technology Leader Jan-Eric Litton (LifeGene, Sweden) -Nomenclature Working Group -Protocols for Data Sharing -Biobank lexicon
Ethics, Governance and Public Engagement Leader Alastair Kent (Genetic Interest Group, UK) -Intellectual Property Policy -Consent form Inter-operability
Epidemiology and Biostatistics Leader Muin Khoury and Julian Little (CDC) -Leader was just appointed first meeting in September
18
P3G Cores
  • Principal work units of P3G,
  • Self-funded,
  • Focused on specific issues related to biobanks,
  • Cores activities are reported to IWG regularly
  • 2006 goals to create cores in areas such as

Questionnaires and Clinical Measures
Population Genetics And Policymaking
DNA/SNPs and Genotyping
Nomenclature
Laboratory Phenotypes
Impact of Commercialization
Environmental Assessment
Federated Databases
Statistics and Epidemiology
Participation Gender Age, Ethnic Differences
19
The P3G Observatory a web-site
describingBiobanks and Population Genetic Studies
  • Isabel Fortier, Ph.D.
  • Vincent Ferretti, Ph.D.
  • Denis Legault, MPA
  • McGill University and Genome Quebec,
  • Innovation Center
  • 740 Dr. Penfield Avenue
  • Montreal (Qc) H3A 1A4

20
The P3G Observatory
  • The Observatory contains
  • a description of studies (57 as of May 29, 2006)
  • a catalog of questionnaires, consent forms, etc.
  • a search tool using key words for common
    variables used in genetic epidemiology
  • a companion tool for questionnaire development
    and harmonization between studies

www.p3gobservatory.org
21
Catalogue of Studies
  • A standard way to describe population studies in
    genomics
  • General Information
  • Background
  • Objectives
  • Methods
  • Status
  • Ethics and Governance
  • Available Documents
  • Publications

57 large population-based studies (P3G members
and non-members)
22 studies with complete information
35 studies with summary information
22
General Tools in Development
DESIGN OF STUDIES
BioBank lexicon
Ethics and governance good practices guidance
documents
ETHICS AND GOVERNANCE
  • General reference procedures for
  • Questionnaires development/collection
  • Physiological measures collection
  • Samples collection, manipulation, storage or
    analysis

INFORMATION COLLECTION/ TREATMENT
Open source information management system for
Biobanks
INFORMATION TECHNOLOGY
Reference tools for statistical analysis and
power calculation
DATA ANALYSIS
23
From Biobanks to improving health and preventing
disease
How do we get from here to there? Meta-studies
enabled by P3G
24
P3G Future Research
25
P3G 2020
  • With the synergy of P3G
  • The scientific community will benefit from having
    a powerful international resource for
    gene-environment studies of complex diseases
  • Return of investment will be quicker, more
    efficient and of higher quality through
    international harmonization
  • Health Care Systems will benefit from accurate
    information for designing and implementing
    population health strategies

26
MERCI
Bartha Knoppers, Leena Peltonen, Andres Metspalu,
Bill Ollier, Eric Wichmann, Jan-Eric Litton,
Julian Little, Muin Khoury, Alistair Kent, Lyle
Palmer, Thomas Hudson, Paul Burton, Claude
Laberge, Isabel Fortier and Mylene Deschenes,
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