Bioinformatic research at Colorado State University has found that stress on the metabolic system forces genes to change how the body converts energy over time, leading individuals toward a progression to type II diabetes.
Dr. Andrey Ptitsyn, the lead researcher on the project, is at Colorado State University's Bioinformatics Center in the College of Veterinary Medicine and Biomedical Sciences. He reexamined previously published data on gene expression, body mass index, cellular oxygen use and insulin resistance of 60-something year old males, some with diabetes, some who were pre-diabetic and some who did not show signs of diabetes. He then repeated the study with two similar data sets and reached the same results. The research will be published this month in the BMC Genomics Journal, a professional biomedical publication.
Using a little-known computer algorithm developed in Russia decades ago, Dr. Ptitsyn, a biomedical and computer expert, has unlocked the path to diabetes as genes of healthy individuals change the way they function - or are expressed. Over time, they begin to resist insulin because cells don't receive enough oxygen during metabolism-related functions.
"Researchers have known for a long time that an individual's oxygen capacity has something to do with diabetes, but until now we didn't know how the two were related. We knew that people who do not have diabetes consume more oxygen compared to people who are pre-diabetic or diabetic," said Ptitsyn. "Even muscle cells of a diabetic don't seem to be absolutely deaf to insulin. We observe elevated activity in genes known to be stimulated by insulin. The cells try to comply with the insulin stimulation, but without a proper oxygen supply, they are confined to a less efficient glycolysis. High expression of certain genes indicates craving for oxygen, but to get oxygen supplied to cells, a person must stimulate capillary growth in the muscles for more blood. Cells continue to be stimulated to expend energy by insulin, but a body can't spend the energy optimally because it lacks oxygen."
The discovery shows that people progress toward the disease as a group of genes switch metabolism - the way a body processes energy - away from aerobic to anaerobic pathways in response to a lack of oxygen. Eventually, cells function much as they would under a state of hypoxia, such as altitude hypoxia, induced when cells are starved for oxygen. The continued state of hypoxia triggers a metabolic syndrome that eventually leads to type II diabetes.
What does this mean for the average person? It means exercise, which develops capillaries that carry oxygen to cells, becomes critical in the fight against diabetes not just for weight control, but because it can dictate how a body uses blood sugar for energy. It also helps scientists understand on the molecular level how individuals develop diabetes and challenges earlier beliefs that a defect in genes controlling oxidation may be the major cause of type II diabetes. Instead, it is more likely that this group of genes fall into disuse altogether with reduction of oxidation in overall energy balance of a cell.
"Our modern, sedentary lifestyle predisposes us for such a loophole in metabolism regulation," Dr. Ptitsyn said. "While physical exercise is a natural way to shift the energy balance to aerobic pathway and improve insulin sensitivity, understanding the molecular mechanisms will allow us to assess individual risks and develop more personalized and effectively aimed drugs to help people. Our study brings us a step closer to this goal."
Dr. Ptitsyn acquired his first experience in classification algorithms in Siberia in late 1980s. As a student, he had a part-time job in a computer lab of Novosibirsk State University, where local scientists taught computational pattern analysis. He became familiar with the inventor of the algorithm that he applied in his current study. This computer algorithm, called FOREL, is little-known among researchers, primarily because it was published only in Russian decades ago and was previously applied in image processing and limited data classification in geology and economics.
FOREL is computationally demanding and, until recently, its application was severely restricted by computer power. However, modifications made by Dr. Ptitsyn significantly improved the performance of the old algorithm, while its ability to operate on high-dimensional data made it particularly suitable for analysis of microarray experiments such as this one, which produce a snapshot of activity for thousands of genes at a time. In collaboration with a team of researchers from the Pennington Biomedical Research Center in Louisiana, Dr. Ptitsyn proposed an alternative analysis and interpretation of the data accumulated in previous experiments.
The original studies that provided the data have made a significant impact on the field of diabetes research. Dr. Ptitsyn's discovery confirms the previously reported findings and reveals new, important details about the data.
"Characteristic patterns of gene expression overlooked in previous studies suggest a different interpretation of the results and point at a different mechanism behind the metabolic syndrome and type II diabetes," Dr. Ptitsyn said. "It is also remarkable that the data acquired in a few independent experiments and made publicly available by the authors can be matched and made to produce new results years after the original publication."