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

Gene Expression Profiling by DNA Chips and Subsequent Bioinformatic Analysis for Identification of Genes and Biochemical Pathways Associated With Type 2 Diabetes

Status

UNKNOWN

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT00143013

Enrollment

100

Registered

2005-09-02

Start date

2004-10-31

Completion date

2007-04-30

Last updated

2008-06-12

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Type 2 Diabetes

Keywords

type 2 diabetes, microarray, skeletal muscle, bioinformatics

Brief summary

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.

Interventions

None listed

Study design

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

30 Years to 65 Years

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

Countries

Denmark

Contacts

Primary ContactVibe Skov, PhD

vibe.skov@ouh.regionsyddanmark.dk

Outcome results