P3G: an international consortium in Human Genome Epidemiology
Ultimate Goals:
For the understanding of gene-environment causes of chronic diseases For better public health strategies
The Causal Complexity of Chronic Diseases
Diabetes Asthma Heart Disease Schizophrenia Cancer Multiple Sclerosis Obesity Arthritis
Genetics
Environment
Diet & Lifestyle
Social Structure
“webs of causation”
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, N ature Review s/Genetics 2005
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
HapMap
P3G
Analytical Tools
Example of Sample Size Issue for detecting ONE interaction for a dichotomous trait and a 10% exposure
Hunter, N ature Review s/Genetics 2005
What 10,000 incident cases in a geneenvironment study can provide:
(with power calculations that that take into account considerations of misclassification of exposure and outcome data, and realistic data collection scenarios)
1. 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.
Prevalence of Environmental Expos ure 0.1 0.2 0.33 0.5 0.1 3.03 2.32 2.15 2.16 Genotype Pre valence 0.2 0.33 2.36 2.11 1.95 1.87 1.80 1.68 1.86 1.70 0.5 2.05 1.78 1.64 1.70
(MDORs; defined as the smallest odds ratio that can be detected at p=10-4 and power=80%).
Paul Burton, UK BioBank Technical Report 2005
What 10,000 incident cases in a geneenvironment 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 > 7). 3. 10,000 cases will provide a powerful platform for genomewide indirect association studies (requiring rigorous definition of statistical significance of p<10-7).
Paul Burton, UK BioBank Technical Report 2005
How long does it take to reach 10,000 cases in a cohort with 500,000 cases?
Breast cancer (F) 17 yrs
Colorectal cancer
Prostate cancer (M) Lung cancer Stroke MI and coronary death
22 yrs
22 yrs 34 yrs 18 yrs 8 yrs
Diabetes mellitus
COPD Hip fracture Alzheimer’s disease Parkinson’s disease
6 yrs
13 yrs 21 yrs 18 yrs 23 yrs
Paul Burton, UK BioBank Technical Report 2005
Public Population Project in Genomics A consortium dedicated to fostering international collaboration between researchers and projects in the field of population genomics
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
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.
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 (Germany)
Estonian Genome Project
LifeGene (Sweden)
NHLBI (USA)
Generations (Scotland)
GenomEutwin
P3G
(Europe) Genoma Espana (Spain) Danubian Biobank Foundation (Europe) LifeLines (Netherlands) CIGMR (UK)
CartaGene (Canada)
NIGM (Mexico)
WAGHP (Australia) ALSPAC (UK)
P3G Membership
3
3
Regular Member Associate Member Individual Member
NEED FOR HARMONIZATION
Analogie: Bill Ollier
HARMONIZATION IS NOT REGIMENTATION
P3G Operational Chart
P3G General Assembly Funders Auditors
P3G Board of Directors
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
P3G Secretariat
Core
Core
Core
Core
P3G OBSERVATORY
International Working Groups (IWGs), leaders and early outcomes
Social, Environmental Leader: and H. Erich Wichmann Biochemical (KORA-Gen, Germany) Investigations Knowledge Curation And Information Technology Leader: Jan-Eric Litton (LifeGene, Sweden) -Common Core Variables for Population Based Studies -Common DNA Quality and Quantity Control -Conceptual model for harmonization of physiologic and biochemical measures -Nomenclature Working Group -Protocols for Data Sharing -Biobank lexicon -Intellectual Property Policy -Consent form Inter-operability
Ethics, Governance and Public Engagement Epidemiology and Biostatistics
Leader: Alastair Kent (Genetic Interest Group, UK) Leader: Muin Khoury and Julian Little (CDC)
-Leader was just appointed: first meeting in September
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:
DNA/SNPs and Genotyping Environmental Assessment Population Genetics And Policymaking Nomenclature Impact of Commercialization Federated Databases Participation: Gender Age, Ethnic Differences
Questionnaires and Clinical Measures Laboratory Phenotypes Statistics and Epidemiology
The P3G Observatory: a web-site describing Biobanks 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
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
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
General Tools in Development
DESIGN OF STUDIES ETHICS AND GOVERNANCE
BioBank lexicon Ethics and governance “good practices” guidance documents General reference procedures for: • Questionnaires development/collection; • Physiological measures collection; • Samples collection, manipulation, storage or analysis
INFORMATION COLLECTION/ TREATMENT
INFORMATION TECHNOLOGY
Open source information management system for Biobanks Reference tools for statistical analysis and power calculation
DATA ANALYSIS
From Biobanks to improving health and preventing disease:
P3G Future Research
P3G Portofolio of Studies:
scler osis
Examples
Canc e phhr e nia r
Schi zo
Athe ro
Arthr it
Colo n
Obes
x x x x x x x x x x x
Biobanks GenomeuTwin Estonian Genome Project Cartagene (Quebec) Generations Scotland LifeGene (Sweden) WAGHP (Australia) NHLBI, NIH, etc. Kora-Gen Danubian Biobank EPIC Others: UK Biobank, Spain, Mexico, Korea, China, etc.
Sample Sizes 100,000 100,000 50,000 50,000 500,000 2,000,000 500,000 20,000 50,000 500,000
x x x x x x x x x
x x x x
x x x x
x x x x x x
x x x x
x x
2,000,000 x
x
x
x
100
other
ity
is
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
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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