Exom-sekvensering for å Identifisere høyrisiko Genvarianter i en Familie Predisponert for Colorectal Cancer
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Colorectal Cancer
- Sponsor
- Norwegian University of Science and Technology
- Enrollment
- 14
- Locations
- 1
- Primary Endpoint
- Data on association between sequence variants in exons and CRC risk
- Status
- Completed
- Last Updated
- 9 years ago
Overview
Brief Summary
The project will use exome sequencing to search for genetic predispositions for familial colorectal cancer (CRC). Except for certain syndromes there is today no good method for identifying individuals with a hereditary high risk for CRC (about 25% of the cases). There is currently no routine screening of the population in Norway for CRC today. Coloscopy, which is the most reliable method, is demanding with respect to resources, it can be painful, and may have complications. This project will attempt to find genetic determinants for identification of individuals with increased risk for familial CRC. Such methods will reduce unnecessary medical examination of unaffected family members, and will make it easier to focus health services on individuals with increased risk. This will represent a significant contribution towards improved health reduced death rate caused by CRC. The project includes research on the ethical aspects, in particular challenges related to how feedback to donors is handled.
Detailed Description
Participants will be from a specific family, and will be selected by invitation to volunteer.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Member of a specific family with increased risk of CRC, including individuals both with and without CRC
Exclusion Criteria
- •Young age
Outcomes
Primary Outcomes
Data on association between sequence variants in exons and CRC risk
Time Frame: Data available within 18 months after recruitment completed
For each participant the genome will be analyzed by exome capture and high throughput sequencing. The exome data will be compared between participants and to reference data for identification of unique variants that can be associated with disease risk.