Validation of a Predictive Risk Equation for Type 2 Diabetes in Families With Risk (DESCENDANCE)

Validation of a Predictive Risk Equation for Type 2 Diabetes in Children With Diabetes to Achieve a Predictive Diagnostic Biochip for the Early Detection of Individuals at Risk in Families.

Considering its epidemic-like development worldwide, associated with modifications in lifestyle, as well as its enormous social and economic weight, the prevention of type II diabetes is certain to be a central concern of health systems within the developed countries in the decades to come. However, while simple obesity concerns the entire population, type 2 diabetes affects only one sub-population at high genetic risk. To be effective and realistic in economic terms, efforts at prevention must be thus targeted towards these subjects at high risk. The key issue involves identifying such subjects early enough so that a strategy of effective prevention can be organized in good time.

Until now, efforts have been concentrated on individuals at risk for diabetes readily identifiable within the general population, typically subjects in the second half of adulthood, presenting abdominal obesity and mild abnormalities of blood sugar. Preventive lifestyle and dietary measures are proposed but are constrictive and difficult to maintain over time, and the results, although they may be significant, remain disappointing, with mere postponement of an outcome which at this stage appears inevitable. The reason is ascribable to excessively tardy intervention, when the pathogenic process has already been ongoing for some ten years and the endocrine function of the pancreas is probably already irreparably impaired.

The alternative thus is earlier intervention, in childhood, adolescence or early adulthood. The problem is to identify individuals at high risk of becoming diabetic at a time when they are presenting no simple clinical or laboratory abnormalities allowing easy diagnosis. The familial character of type 2 diabetes is now well established, and future diabetic subjects are themselves above all the children of diabetic subjects. However, the prevalence of the disease among the descendants of type 2 diabetic subjects is around 20-30% and predictive tools are needed to combat diabetes in these high-risk families.

We propose to create a risk equation using an algorithm to reliably predict children most likely to develop diabetes later in life.

The algorithm will include 3 classes of data:

  • The genotype stemming from the genetic characterization of individuals and those their parents;
  • Environmental data concerning childhood, especially eating habits and physical activity;
  • Data of the mother who was eventually diabetic during pregnancy.

From a methodological standpoint, it would be rather difficult to take blood samples from children and wait some 50 years to determine whether or not they develop diabetes. To circumvent this difficulty, we will recruit subjects in families with a history of type II diabetes:

  • Parents alive, including at least one type 2 diabetic subject
  • Adult children (aged over 35 years), some of whom are already presenting type II diabetes, and healthy brothers and sisters, who form the control population. Test will be done to determine whether healthy subjects are really safe from the risk of diabetes (HbA1c measurement and glucose load test).

The Descendence study will include 500 families at risk involving about 3000 subjects (1000 subjects with diabetes and 2000 healthy subjects). It is expected to answer the following question: for a child born in such families at risk, what is the probability of developing diabetes later in life, so that early preventive action may be taken

Study Overview

Status

Completed

Conditions

Study Type

Interventional

Enrollment (Actual)

1035

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

      • Liege, Belgium, 4000
        • CHU Sart Tilman Liege
      • Besancon, France, 25030
        • Chu Jean Minjoz
      • Bobigny, France, 93000
        • CHU Avicenne
      • Bondy, France
        • CHU de Bondy
      • Brest, France
        • CHU de Brest
      • Caen, France, 14000
        • CHU de Caen
      • Evry, France, 91000
        • Ch Sud Francilien
      • Grenoble, France, 38043
        • University Hospital Grenoble
      • Le Kremlin-Bicêtre, France, 94270
        • CHU de Bicetre
      • Lille, France, 59037
        • CHRU Lille
      • Marseille, France, 13274
        • CHU Marseille Hôpitaux Sud
      • Nancy, France, 54500
        • CHU de Nancy
      • Nantes, France, 44000
        • Chu de Nantes
      • Paris, France, 75877
        • CHU Bichat
      • Reims, France
        • CHU de Reims
      • Strasbourg, France, 67000
        • Centre Hospitalier Strasbourg
      • Toulouse, France, 31403
        • CHU Toulouse

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

25 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Inclusion Criteria:

  • Families at risk for diabetes defined by the existence of the disease in two successive generations and consists with healthy subject in the two generations.
  • Subjects must be aged over 25 years

Exclusion Criteria:

  • subject refusing to participate
  • pregnant women

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Prevention
  • Allocation: Non-Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Other: Type 2 diabetic subject
Subject with type 2 diabetes
Other: healthy subject
Healthy subjet from family where there is the existence of the disease (type 2 diabetes) in two successive generations
Oral Glucoce Tolerance Test

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Measure of risk of developing type 2 diabetes in at-risk families
Time Frame: participants will be followed from the moment where they sign consent form and until they have sent back questionnary and done the blood test, an expected average of 4 weeks
Oral Glucose Tolerance Test (only for health volunteers) HbA1c assay (for type 2 diabetic subject)
participants will be followed from the moment where they sign consent form and until they have sent back questionnary and done the blood test, an expected average of 4 weeks

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

December 14, 2011

Primary Completion (Actual)

November 24, 2020

Study Completion (Actual)

November 24, 2020

Study Registration Dates

First Submitted

November 8, 2012

First Submitted That Met QC Criteria

November 12, 2012

First Posted (Estimate)

November 16, 2012

Study Record Updates

Last Update Posted (Actual)

May 11, 2021

Last Update Submitted That Met QC Criteria

May 7, 2021

Last Verified

August 1, 2020

More Information

Terms related to this study

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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