What is the study about?
It provides comprehensive genomic, clinical, behavioural and environmental data on 330,000 Canadians for the global research community to produce evidence to establish health-related policies.
CanPath has collected data from approximately 330,000 volunteer Canadians, including information about health, lifestyle, environment and behaviour.
The size of the cohort and the richness of its epidemiological, clinical and biological data positions Canada amongst the world’s leaders in longitudinal cancer and chronic disease research.
Large subsets of participants have also provided physical measures, mental health measures, magnetic resonance imaging (MRI) data and biological samples such as blood and urine.
The power of this cohort will increase with time as new data are added, technology advances, and incident health outcomes are captured.
A Harmonized Research Platform
Researchers can link harmonized and de-identified health and biological information to provincial and national administrative data repositories to support pan-Canadian research.
Baseline data from five regional cohorts have been harmonized across the country, creating a pan- Canadian resource of more than 1,600 measures of participant health and lifestyle factors.
The cohort is designed to facilitate collaboration with other large-scale international research initiatives, such as the UK Biobank or the European Prospective Investigation into Cancer and Nutrition (EPIC) study.
Most participants have agreed to the linkage of their questionnaire and biospecimen data to their administrative health records and are open to being re-contacted for ancillary studies by their regional cohorts to collect additional data and samples.
CMAJ Marker Paper
Additional information can be found in the June 2018 marker paper that was published in the Canadian Medical Association Journal.CMAJ Marker PaperOpen
What information can you find?
Tracked Diseases to Date
Enriching the Data
Biological samples from a subgroup of participants will undergo genetic testing (genotyping) to examine single nucleotide polymorphisms or SNPs (specific sections of their DNA) that are of interest in disease research.
CanPath has genotyped close to 50,000 participants.
CanPath has stored biospecimens that can support researcher access requests for modern interrogations of individual cells. By the end of 2020, more than three million single-cell interrogations will have been completed. All of these CanPath data are available to researchers. Requests are also increasing for the use of plasma and serum for cell-free biomarker development, metabolomics and proteomics with funding from the CIHR and CFI.
Links to health-care administrative data
In a secure manner and with participants’ consent, the regional cohorts of CanPath will obtain additional information on the participants’ health from health care administrative databases, providing researchers with an overview of participants’ use of health services, such as physician visits or hospitalizations, and health outcomes, such as new diagnoses of cancer.
Cross-Cohort Harmonization Project for Tomorrow (CHPT)
Launched in 2015, Cross-Cohort Harmonization Project for Tomorrow (CHPT) is a research network led by Montreal-based Maelstrom Research of McGill University. The project brings together a number of selected North American and European cohort studies focused on better understanding the risk factors that contribute to cancer and other major chronic diseases. CHPT currently includes 13 large cohort studies; listed among them are CanPath, UK-Biobank, Nurses’ Health Study, and LifeLines Cohort Study and Biobank. Through this collaboration of international cohorts, CHPT has created a catalogue of searchable metadata (information on the types and amounts of data available) on over 2.5 million participants.
More information on CHPT can be found on Maelstrom Research’s site.
Emerging opportunities in artificial health (AI)
Sequencing the whole genomes of every CanPath participant represents a huge opportunity to support Canadian research, infrastructure development and training. Combined with more than 1,000 variables of information captured from each participant, together these high-quality big data sets will be critical to support the application of advanced AI methods to improving health.
With collaborations at major institutes like the Vector Institute in Toronto and MILA-Quebec AI Institute, CanPath is well-positioned to support AI innovations in health research that require data on hundreds of thousands of individuals.
CanPath leadership are highly motivated to support the generation of a genomics data platform that can support made-in-Canada research and innovation. Discussions are ongoing with potential public and private partners to place Canada in the same tier as other genetically well-characterized cohorts while emphasizing its unique demography, geography and resources.
Canadian Urban Environmental Health Research Consortium (CANUE)
CANUE is a CIHR-funded research platform that collates and generates standardized area-level environmental data on air and noise pollution, land use, green/natural spaces, climate change/extreme weather, and socioeconomic conditions and links this data to existing Canadian cohort studies (including CanPath) as well as administrative health databases.
CANUE datasets, which are indexed to every postal code in Canada, enrich CanPath’s existing information on individual lifestyle, health, and risk factors, physical measures and biosamples.
This information will be of interest for a wide range of studies, including those investigating the impacts of the urban environment on health, for example – that of local air quality, access to green spaces, opportunities for walking and cycling, noise and light pollution levels, and climate factors on the aetiology of specific health outcomes and population health.
CANUE datasets available on the CanPath Data Portal include:
• Canadian Active Living Environments Database (Can-ALE)
• Material and Social Deprivation Index
• Normalized Difference Vegetation Index (NDVI; i.e. “greenness” metrics)
• Annual average nitrogen dioxide (NO2) exposure
• Annual average ozone (O3) exposure
• Annual average fine particulate matter (PM2.5) exposure
• Annual average sulfur dioxide (SO2) exposure
• Weather and Climate metrics
• Satellite based nighttime light