Objective
Summary
Insulin dependent diabetes (IDDM) is a multifactorial disease characterised by autoimmune destruction of pancreatic islet beta cells.
Its incidence is increasing and IDDM is now one of the fastest growing diseases of young people. There are strong genetic and environmental causal components to the disease with siblings of cases having 15 times the risk of the general population of developing the disease. Regions of the genome which account for less than half of the familial risk have been identified to date. Mapping the remaining regions is limited by the large sample sizes required. Reducing the burden of diabetes complications is a major public health challenge. Some of the complications of IDDM show familial clustering and are thought to be under separate genetic control. The degree of this clustering requires quantification and the genes have yet to be mapped. Understanding the genetic basis of IDDM complications will lead to improved treatment and prevention. The collection of a sample of adequate size to advance these studies necessitates concerted action across Europe.
Objectives of the study
1. To map the genes which determine IDDM among European populations. 2. To quantify the degree of familial clustering of the IDDM complications, nephropathy, retinopathy and cardiovascular disease in a European cohort. 3. To map the genes responsible for the clustering of IDDM complications in this cohort.
4. To study the interaction between environmental factors and genetic determinants of IDDM complications in Europe.
5. To provide a repository of DNA samples for use by other European investigators in replication and validation studies.
Proposal content
A cross sectional survey of 3250 people with IDDM in 29 centres in Europe was funded by the European Community in 1989-91 and a follow up study of this cohort was funded within the BIOMED programme in 1996 (The EURODIAB Prospective Complications Study). This study involves tracing the survivors of the original cohort who will respond to a questionnaire about lifestyle factors, medication and nutrition and undergo a physical examination to quantify diabetic complications and glycaemic control. We propose a conjunctive family study which will build on the infrastructure of EURODIAB PCS. In the original cohort 10% of respondents reported that they had a sibling with diabetes. We propose to invite these siblings, and any further siblings ascertained at follow up (total = 240), for interview and clinical examination. In addition each centre will screen routine diabetes clinic attenders for sibling history of IDDM, providing a further 260 affected pairs. The degree of familial clustering of diabetic complications will be quantified.
Blood from the original participants, the affected siblings and their parents will be taken for genetic analysis. A semi - automated genome wide scan using 340 markers with non parametric affected sibling pair (ASP) analysis will be used to map loci which determine IDDM and loci which determine IDDM complications. These methods will locate loci to within a genetic distance of 10 centimorgans (cM). The linkage of specific candidate genes implicated in the development of IDDM and diabetic complications will also be studied. Among families in which at least one parent is available, a family-based association design using the transmission disequilibrium test will be used both for candidate genes, and for regions of interest identified by the total genome scan, in order to achieve fine resolution mapping of the genetic effect in these regions.
Lymphoblastoid cell lines will be established on this family material, to provide a repository for other European researchers.
The detailed environmental data, such as blood pressure and glycaemic control, collected on the original cohort and repeated at follow up will be used both to stratify ASPs into phenotypic subgroups and to assess the degree of genotype environment interaction in the development of diabetic complications.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- medical and health sciencesbasic medicinepharmacology and pharmacypharmaceutical drugs
- medical and health sciencesclinical medicineendocrinologydiabetes
- medical and health sciencesclinical medicinecardiologycardiovascular diseases
- medical and health sciencesclinical medicineophthalmologyretinopathy
- medical and health sciencesmedical biotechnologytissue engineeringartificial pancreascontinuous glucose monitors
You need to log in or register to use this function
Topic(s)
Data not availableCall for proposal
Data not availableFunding Scheme
CSC - Cost-sharing contractsCoordinator
WC1E 6BT London
United Kingdom