Genetic and Environmental Risk Factors of Type 1 Autoimmune Diabetes and Its Early Complications

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

20000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2004-11-30

Study Completion Date

2018-06-30

Brief Summary

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The aim of this study is to complete the identification of genetic factors (G) and to undertake the search of environmental factors (E) predisposing to type 1 diabetes (T1D) by constituting a cohort of 3500 T1D patients and a control cohort. We will use the base of G analysis (whole genome genotyping done once a patient using methods conually updated at Centre National de Genotype) and innovative E analysis to develop the following long term objectives :

* Identify G and E factors influencing the process of remaining beta cells' destruction during the first 3 years after diagnosis (subgroup of T1D patients with a 0-3 years diabetes duration);
* Identify G factors (pharmacogenomics) of the individual response to insulin using the effective insulin dose as a phenotype over a period of 2 years (subgroup of T1D patients with negative C-peptide and well managed diabetes);
* Undertake a prospective research of G and E risk factors of "death in bed" syndrome in diabetic adolescents;
* Undertake a prospective research of G and E risk factors of incipient glomerular microangiopathy (regule measurement of microalbuminuria).

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Detailed Description

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Still recognized in youth only at a stage of complete beta-cell mass destruction and insulin deficiency, autoimmune T1D remains a source of major morbidity through daily life and chronic angiopathic complications despite a better glycemic control. T1D onset is now predominantly pediatric, since its incidence shows a rapid and continuous increase in young European children, due to unknown emerging environmental changes, creating a major need for discoveries in the environmental field. Finding avoidable E factors can allow T1D prevention in the whole children population. Lack of infectious exposures ("the hygiene hypothesis"), viruses, early nutrition, or other factors have been suspected, but E causes of T1D remain a black box, as for most human diseases, that should now be approached more systematically and with respect to gene-environment interactions.

The aim of our study is to complete the identification of genetic factors (G) and to undertake the search of environmental factors (E) predisposing to type 1 diabetes (T1D) by constituting a cohort of 3500 T1D patients and a control cohort. We will use the base of G analysis (whole genome genotyping done once a patient using methods conually updated at Centre National de Genotype) and innovative E analysis to develop the following long term objectives :

* Identify G and E factors influencing the process of remaining beta cells' destruction during the first 3 years after diagnosis (subgroup of T1D patients with a 0-3 years diabetes duration);
* Identify G factors (pharmacogenomics) of the individual response to insulin using the effective insulin dose as a phenotype over a period of 2 years (subgroup of T1D patients with negative C-peptide and well managed diabetes);
* Undertake a prospective research of G and E risk factors of "death in bed" syndrome in diabetic adolescents;
* Undertake a prospective research of G and E risk factors of incipient glomerular microangiopathy (regule measurement of microalbuminuria).

We propose to constitute a French multicentric cohort of T1D patients, well phenotyped by 3 data types : genetic, environmental and clinical data. The data collection scheme includes at entry a comprehensive 850 items environmental questionnaire for all subjects and a full genotyping with at least 500,000 SNPs until whole-genome sequencing can be deployed by CNG-CEA. Every 6 months, a standardized clinical assessment is made in patients (a WEB application ensuring this standardization has already been developed). Personal address(es) will be collected and geocoded, then mapped with environmental geographic information systems (GIS).

With environmental modelling, the high dimensionality analyses (HDA) constitutes one of the main originality of ISIS-DIAB approaches of translational research. HDA will face not only a massive mass of data, but data of a remarkable diversity (genomic variants, environmental items from questionnaires, environmental data bases mapped to patient address, space-time items, characteristics of social environment, clinical phenotypes etc). A given genotype (defined by many genomic variants) will predispose to T1D only in a given environmental context (defined possibly by a number of factors) and induce a given type of autoimmune process (age of onset, rate of destruction, biomarkers). Since T1D is both multifactorial and heterogeneous, causal factors may interact in a considerable number of scenarii, thus platforms which study these factors should obviously interact. Without HDA, each platform would be left faced with its own data. The chef d'orchestre has to be HDA, to integrate the massive amounts of data and draw networks of causality. Technological advances in HDA developed in other fields of sciences, business and economics (forecasting technology) will be transferred to biomedical research through ISIS-DIAB. French have a strong tradition of high-level maths in this area. We designed the ISIS-DIAB cohort and collection of data to feed HDA with multidisciplinary data. In ISIS-DIAB program, HDA will identify the variables that have the most predictive value on several outcomes (not confined to T1D causality).

Conditions

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Diabetes Mellitus Insulin-Dependent

Study Design

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Observational Model Type

CASE_CONTROL

Study Groups

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Isis-Diab patients

French T1D patients with genetic data (GWAS), and environmental data (questionnaire and environmental databases), clinical data

Collect of environmental data on T1D patients before diagnosis

Intervention Type OTHER

Questionnaires on large environment during mother's pregnancy and patient's childhood, health book copies, addresses' geolocation, quantification of viral exposures using Sentinel Network data

Collect of blood samples for DNA extraction and genetic characterization (GWAS)

Intervention Type GENETIC

Collect of blood samples for DNA extraction and genetic characterization (GWAS) on Illumina platform (Centre National de Genotype)

Collect of clinical data on the disease and its evolution

Intervention Type OTHER

Collect of clinical data on the disease and its evolution every 6 months after enrollment

Isis-Diab controls

French control population with genetic data (GWAS) and environmental data (questionnaire and environmental databases

Collect of environmental data on French controls (age-matched for T1D patients)

Intervention Type OTHER

Questionnaires on large environment during mother's pregnancy and patient's childhood, health book copies, addresses' geolocation, quantification of viral exposures using Sentinel Network data

Collect of blood samples for DNA extraction and genetic characterization (GWAS)

Intervention Type GENETIC

Collect of blood samples for DNA extraction and genetic characterization (GWAS) on Illumina platform (Centre National de Genotype)

Interventions

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Collect of environmental data on T1D patients before diagnosis

Questionnaires on large environment during mother's pregnancy and patient's childhood, health book copies, addresses' geolocation, quantification of viral exposures using Sentinel Network data

Intervention Type OTHER

Collect of blood samples for DNA extraction and genetic characterization (GWAS)

Collect of blood samples for DNA extraction and genetic characterization (GWAS) on Illumina platform (Centre National de Genotype)

Intervention Type GENETIC

Collect of clinical data on the disease and its evolution

Collect of clinical data on the disease and its evolution every 6 months after enrollment

Intervention Type OTHER

Collect of environmental data on French controls (age-matched for T1D patients)

Questionnaires on large environment during mother's pregnancy and patient's childhood, health book copies, addresses' geolocation, quantification of viral exposures using Sentinel Network data

Intervention Type OTHER

Collect of blood samples for DNA extraction and genetic characterization (GWAS)

Collect of blood samples for DNA extraction and genetic characterization (GWAS) on Illumina platform (Centre National de Genotype)

Intervention Type GENETIC

Eligibility Criteria

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Inclusion Criteria

* Insulin-dependent diabetes
* Patients older than 6 months at inclusion
* European or North African geographical origin (defined by the birthplaces of the 4 grandparents), for the purpose of genetic homogeneity of the cohort
* Anti-GAD, IA2, and insulin autoantibodies, that are present only in the first year of the disease evolution, are not a criterion of absolute inclusion (low risk of error) but will be noted if they were searched at diagnosis
* Informed consent dated and voluntarily signed (patient and/or parents)