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Gene Expression Profiling and Bioinformatic Analysis Identifying Genes and Biochemical Pathways in Type 2 Diabetes

The recruitment status of this study is unknown. The completion date has passed and the status has not been verified in more than two years.
Verified June 2008 by Odense University Hospital.
Recruitment status was:  Recruiting
Information provided by:
Odense University Hospital Identifier:
First received: September 1, 2005
Last updated: June 11, 2008
Last verified: June 2008

Type 2 diabetes is a disorder of the metabolic system that greatly affects individual health and imposes significant cost for society on health care. It is necessary to initiate research with emphasis on improvement on quality of life and reduce the serious complications as a result of type 2 diabetes.

In type 2 diabetes insulin resistance and impairment of insulin secretion by beta-cells are the major pathophysiological defects and characterized by raised plasma glucose levels. Today, little is known about gene regulation and biochemical pathways involved in the disease.

Bioinformatics and gene expression microarrays (GEM) will be applied to gain insight into the molecular pathophysiology of type 2 diabetes. The simultaneous monitoring of thousands of genes in parallel can identify novel genes and entire biochemical pathways that are dysregulated at the transcriptional level. Affymetrix Inc. chips or spotted arrays will be applied as DNA microarray tools. Bioinformatic software programs and databases will be employed as data mining tools in order to perform statistical analysis, cluster analysis and biochemical pathway analysis.

Biopsies from skeletal muscle and adipose tissue from both diabetics and nondiabetics will be applied. Changes in genes and biochemical pathways between diabetics and nondiabetics and functional relationships between adipose tissue and skeletal muscle will be investigated.

Grouping of subtypes in type 2 diabetes will be performed and a classification system will be constructed. Building a classifier may provide better and more precise diagnosis of type 2 diabetes.

Major advances in health science of type 2 diabetes thus seems to be promising and paving the way for individual treatment based on a more precise diagnosis.

Type 2 Diabetes

Study Type: Observational
Study Design: Time Perspective: Prospective
Official Title: Gene Expression Profiling by DNA Chips and Subsequent Bioinformatic Analysis for Identification of Genes and Biochemical Pathways Associated With Type 2 Diabetes

Resource links provided by NLM:

Further study details as provided by Odense University Hospital:

Estimated Enrollment: 100
Study Start Date: October 2004
Estimated Study Completion Date: April 2007

Ages Eligible for Study:   30 Years to 65 Years   (Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes

Inclusion Criteria:

Of diabetic subjects:

  • Type 2 diabetes
  • Age: 30-65 years
  • BMI: 27-35

Of nondiabetic subjects:

  • Age: 30-65 years
  • BMI: 27-35

Exclusion Criteria:

Of diabetic subjects:

  • Medication, which have any influence on glucose metabolism and gene expression in adipose tissue and skeletal muscle at the time of sampling of biopsies.
  • Disease in liver, heart, vessels or endocrine organs

Of nondiabetic subjects:

  • Type 2 diabetes
  • Relatives with type 2 diabetes
  • Hyperglycemia
  • Medication, which have any influence on glucose metabolism and gene expression in adipose tissue and skeletal muscle at the time of sampling of biopsies.
  • Disease in liver, heart, vessels or endocrine organs
  Contacts and Locations
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Please refer to this study by its identifier: NCT00143013

Contact: Vibe Skov, PhD

Department of Clinical Biochemistry and Genetics, KKA Recruiting
Odense C, Funen, Denmark, 5000
Contact: Vibe Skov, MSc    +45 6541 2837   
Sponsors and Collaborators
Odense University Hospital
Principal Investigator: Vibe Skov, MSc Odense University Hospital
  More Information Identifier: NCT00143013     History of Changes
Other Study ID Numbers: 002
Study First Received: September 1, 2005
Last Updated: June 11, 2008

Keywords provided by Odense University Hospital:
type 2 diabetes
skeletal muscle

Additional relevant MeSH terms:
Diabetes Mellitus
Diabetes Mellitus, Type 2
Glucose Metabolism Disorders
Metabolic Diseases
Endocrine System Diseases processed this record on May 23, 2017