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Diabetes Genome Anatomy Project |
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Projects > Project 2
Project 2: Identifying the underlying alterations in gene expression which result in type 2 diabetes
Primary Investigator: Mary-Elizabeth Patti, M.D. (Joslin Diabetes Center)
Co-Investigator: Allison B. Goldfine, M.D. (Joslin Diabetes Center)
Specific Aims
- To create a map of gene expression across the diabetes metabolic spectrum
by quantitating gene expression in the fasting state in skeletal muscle biopsy
specimens from human subjects across a broad range of insulin sensitivity (Si),
as classified by intravenous glucose tolerance testing (IVGTT) and minimal
model analysis.
- To identify genes whose expression is altered in response to acute in vivo
insulin stimulation (euglycemic clamp) in human skeletal muscle, and to compare
the type and magnitude of insulin-mediated changes in subjects chosen from
across the metabolic spectrum (as defined in Specific Aim 1) in order to
define: (a) insulin-regulated genes in insulin sensitive subjects and (b)
defects in the ability of insulin to modulate expression in insulin resistant
and diabetic subjects.
- To assess time stability of gene expression by analyzing repeated biopsy
samples of skeletal muscle in subjects with varying degrees of insulin
resistance 2-3 years after initial biopsy and correlate with changes in
metabolic control over time, in order to identify genes which predict declining
metabolic control and development of diabetes.
Summary
The overall goal of this project is to identify the underlying alterations in
gene expression which result in type 2 diabetes. Though details of disease
pathogenesis are increasingly complex, epidemiologic studies in humans have
clearly defined risk factors for the development of and/or progression of
diabetes, including: (1) genetics/family history, resulting in alterations in
primary gene sequence, and (2) both prenatal and postnatal environmental
factors, including suboptimal intrauterine environment and low birth weight,
obesity, nutrient excess (even in the absence of obesity), inactivity,
gestational diabetes, and advancing age (Figure). Each of these risk factors
can, via largely undefined mechanisms, lead to skeletal muscle, adipose, and
hepatic insulin resistance, ?-cell dysfunction, and overt diabetes. In turn,
diabetes-related hyperglycemia and associated metabolic abnormalities can
further alter signal transduction and gene expression, thus contributing to a
vicious cycle.
We hypothesize that each of these risk factors alters gene expression, likely
in a unique but partially overlapping way, and that the superimposition of
multiple risk-related changes in gene expression are likely to be the final
common pathway by which both variations in primary gene sequence and
environmental factors mediate diabetes risk. Since the earliest detectable
abnormality in subjects at risk for type 2 diabetes is insulin resistance in
skeletal muscle, we are using oligonucleotide arrays to analyze expression of
both known and potentially novel genes and EST in skeletal muscle biopsy
specimens from metabolically characterized human subjects across the spectrum
of metabolic stages of diabetes, ranging from normal insulin sensitivity to
insulin resistance to overt diabetes.

Primary Investigator
The long-range goal of our laboratory investigation is to define molecular
mechanisms by which changes in gene expression resulting from primary gene
sequence or the metabolic/nutritional environment mediate risk for type 2
diabetes in humans. We hypothesize that diabetes risk factors, including family
history, low birth weight, and obesity, alters gene expression, likely in a
unique but partially overlapping way, and that the superimposition of multiple
risk-related changes in gene expression are likely to be the final common
pathway by which both variations in primary gene sequence and environmental
factors mediate diabetes risk. (See project 2 summary.) Therefore, our
laboratory is utilizing genomics approaches, including high-density
oligonucleotide arrays and restriction-based differential display, to identify
alterations in gene expression which confer diabetes susceptibility.
Since insulin resistance is the earliest observable metabolic defect in the
majority of prediabetic subjects, we have focused our efforts primarily in
skeletal muscle and adipose tissue from metabolically characterized human
subjects at risk for diabetes on the basis of family history, obesity, and low
birth weight to identify primary, potentially pathogenic changes in gene
expression. While we are using human tissues in metabolically characterized
individuals whenever possible for primary data, refinement and confirmation of
hypotheses are performed in cell culture and animal models. Clearly, validation
and functional characterization of diabetes risk genes identified from
differential gene expression studies will be a major endeavor over the next few
years.
Co-Investigator
Dr. Goldfine is the clinically focused co-investigator for project 2. Research
investigations in Dr. Goldfine's lab focus on clinical and molecular
translational projects related to insulin action and development of type 2
diabetes and molecular mechanisms of drug action. Current work for the DGAP
project involves careful phenotyping of insulin sensitivity and beta-cell
function of subjects with risk factors for type 2 diabetes to allow
characterization of physiologic determinants of disease and to obtain tissue
for genomic analysis. Dr. Goldfine also has ongoing projects to explore
mechanisms of cardiovascular complications of diabetes through evaluation of
endothelial dependent and endothelial independent vasodilation as influenced by
hyperglycemia or hyperinsulinemia, the effects of antioxidants on restoring
endothelial function, and the role of hormone replacement therapy on vascular
function. Additional clinical trials are in progress to evaluate clinical and
molecular mechanisms of drug targets in key pathways regulating insulin
sensitivity, including peroxisome proliferator activated receptor-? (PPAR?) and
insulin resistant kinase IRK (also known as IKK) and NFkB pathways.
Protocols
Microarray Data
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