Feldman, Eva , PhD
Diabetic dyslipidemia: a new therapeutic target for diabetic neuropathy
General Research Subject: Both Type 1 And Type 2 Diabetes
Focus: Complications, Complications\Neuropathy, Diabetic Dyslipidemia, Obesity, Obesity\Animal Models
Type of Grant: Basic Science
Project Start Date: July 1, 2012
Project End Date: June 30, 2015
Diabetic neuropathy (DN) is a common and debilitating complication of type 2 diabetes. The ADA recently supported systematic analyses of all available data, including blood work and nerve biopsies, collected from human subjects as part of a clinical trial for the treatment of DN. Unexpectedly, these analyses revealed that elevated triglycerides were a more important predictor of DN than elevated glucose. These results suggest a new idea: that a network of metabolic changes in type 2 diabetes, centered on dyslipidemia, predicts the onset and progression of DN.
In the current proposal, gene expression data sets from human sural nerves from type 2 subjects with DN, and sciatic nerves from mouse models of type 2 DN, will be analyzed using bioinformatics methods to confirm that changes in lipid metabolism most robustly predict progressive DN. The localization, expression, and regulation of lipid pathway genes and proteins will then be examined in the sciatic and sural nerves of two mouse models of type 2 diabetes and DN. In parallel, lipid metabolites will be screened in the mouse models to identify lipid related molecules in blood and/or urine that could then be used to identify patients at risk for developing DN and identify new targets for future human studies.
Our studies challenge the current paradigm that high glucose is the primary driver of DN and identify high lipids as an equally, if not more important, cause of DN in type 2 diabetes. This has substantial therapeutic importance and could significantly change current treatment regimens.
What area of diabetes research does your project cover? What role will this particular project play in preventing, treating and/or curing diabetes?
I am actively engaged in understanding the causes of and potential therapies for diabetic neuropathy (DN), the most prevalent complication associated with diabetes. Currently, there are no effective treatments for DN, as it often remains undetected until it has progressed to a state where treatment would be minimally effective. The identification of non-invasive DN biomarkers would greatly enhance our understanding of early events that occur in DN and aid in our ability to predict DN development and rate of progression.
Hemoglobin A1c (HbA1c), a biomarker of diabetes, is a direct indicator of glycemic control. Biomarkers of diabetic nephropathy, microalbuminuria and creatinine measured in urine, directly reflect kidney function. To date, however, no such biomarkers exist for DN. As a consequence, this complication often develops unchecked until symptoms and signs indicative of irreparable damage appear. The current project aims to identify DN biomarkers potentially associated with lipid metabolism, which has been found to be closely associated with the progression of DN. Early diagnosis equals early treatment and the potential slowing or prevention of this complication.
If a person with diabetes were to ask you how your project will help them in the future, how would you respond?
Scientists and clinicians who study diabetic neuropathy (DN) have collected a lot of data over the years relating DN to other measures of diabetes, including glycemic control and duration of diabetes. So far, they have not been able to reliably predict who will develop this complication or when this complication begins. What we hope to identify are changes in genes and proteins that tell us when peripheral nerves are under stress prior to the development of pain or loss of sensation, the major symptoms of DN. Once loss of sensation happens, it is almost impossible to regrow the connections. If we identify and treat the nerves before these connections are lost, we would be able to prevent nerve loss and may even be able stimulate growth.
We recently identified genes that are altered in human DN and developed computational models based on their expression to predict future progression. The proposed project will further identify and validate potential biomarkers that may be useful for the diagnosis and therapeutic management of human DN using both human and animal models.
Why is it important for you, personally, to become involved in diabetes research? What role will this award play in your research efforts?
As a Neurologist, I frequently see patients who have lost sensation in their feet as a result of diabetic neuropathy. Numb feet are more likely to be injured and these injuries are often unnoticed until the wound becomes infected. These infections, combined with poor healing associated with diabetes often result in amputation of toes, feet and the lower leg. In fact, diabetic neuropathy is the leading cause of non-traumatic amputations in the United States.
Our proposal will examine genes and proteins in neuronal tissues from humans and mice affected by diabetes. Analyzing genes in large scale, however, is expensive. This ADA funding will cover these costs and provide salary support for the biologist and the computer expert needed to generate and analyze these data. Advanced technology allows us to look at how tens of thousands of genes are being regulated simultaneously. However, only a small fraction of these changes are likely to lead to the identification of biomarkers. Using high speed computing and specialized statistics, a combination called "bioinformatics," we can identify the most promising genes much more quickly than using conventional methods. By increasing the pace of our research, we shorten the time that patients must wait for new and needed treatment.
In what direction do you see the future of diabetes research going?
Bioinformatics enables us to quickly compare tens of thousands of genes and find similarities and differences among complication-prone tissues by combining multiple levels of information (eg. genes, proteins, metabolites, etc. in a "systems biology" approach), to better understand the pathophysiology and mechanisms underlying diabetic complications. This technology also extends towards identifying small genetic differences in patients that may predict if they will develop complications and what kind. The term "personalized medicine" is used to describe how understanding an individual’s unique set of genes relates to their chances of developing a disease or condition and how they would respond to specific treatments. We already know that certain conditions "run" in families; understanding the biology behind this phenomenon and how it is affected by lifestyle and environment will help patients take health into their own hands.
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