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

NCT ID: NCT00143013

Last Updated: 2008-06-12

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

100 participants

Study Classification

OBSERVATIONAL

Study Start Date

2004-10-31

Study Completion Date

2007-04-30

Brief Summary

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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.

Detailed Description

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Conditions

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Type 2 Diabetes

Keywords

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type 2 diabetes microarray skeletal muscle bioinformatics

Study Design

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Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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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
Minimum Eligible Age

30 Years

Maximum Eligible Age

65 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Odense University Hospital

OTHER

Sponsor Role lead

Principal Investigators

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Vibe Skov, MSc

Role: PRINCIPAL_INVESTIGATOR

Odense University Hospital

Locations

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Department of Clinical Biochemistry and Genetics, KKA

Odense C, Funen, Denmark

Site Status RECRUITING

Countries

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Denmark

Central Contacts

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Vibe Skov, PhD

Role: CONTACT

Email: [email protected]

Facility Contacts

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Vibe Skov, MSc

Role: primary

Other Identifiers

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002

Identifier Type: -

Identifier Source: org_study_id