Type 2 diabetes: a cellular metabolism problem

By Heather Buschman, Ph.D.
January 10, 2013

A new computational model of sugar transport in the pancreas reveals a metabolic “tipping point” in type 2 diabetes—a discovery that may form the basis for new efforts to prevent and treat the disease.

Changes in cellular metabolism play a bigger role in the development of type 2 diabetes than previously thought—perhaps an even larger part than genetic predisposition plays in the disease. That’s what Sanford-Burnham and UC Santa Barbara researchers concluded in a study published recently in the journal PLOS ONE. The team, including Jamey Marth, Ph.D., developed a computational model to better understand the underlying causes and progression of type 2 diabetes. The model revealed a metabolic “tipping point” that, when crossed, prevents the pancreas from adequately sensing blood sugar and secreting insulin. The team expects the discovery will form the basis for new efforts to prevent and treat type 2 diabetes.

Type 2 diabetes

Type 2 diabetes is a chronic condition in which blood sugar (glucose) levels are high. Normally, beta cells in the pancreas continually “sample” the bloodstream to keep tabs on glucose levels. When they sense a rise in blood glucose (such as after a meal), beta cells secrete insulin to keep levels from getting too high. But in type 2 diabetes, beta cells fail to execute this important function. As a result, blood glucose levels rise, wreaking havoc on blood vessels and other organ systems.

Obesity has long been linked to type 2 diabetes, but the cellular origin of the disease due to beta cell failure has not been described until now. “In obesity, there’s also a lot of fat in the system,” said Marth. “When beta cells are exposed to high levels of fat, their glucose transport mechanism breaks down. That’s how the environment plays a role, even among large segments of the population who are genetically ‘normal.’” Marth is a professor at Sanford-Burnham and UC Santa Barbara, where he holds the John Carbon Chair in Biochemistry and Molecular Biology and the Duncan and Suzanne Mellichamp Chair in Systems Biology.

Simulating glucose transport

In this latest study, Marth and colleagues developed a mathematical model to track how beta cells take up, or sample, glucose in the bloodstream. The model uses data from normal and diabetic donors, as well as supporting information from rodent studies.

The model revealed a glucose “tipping point.” In a healthy person, beta cells take in enough glucose to stay above the threshold. In type 2 diabetics, however, the amount of glucose transported into beta cells drops below the tipping point. That’s why the cells don’t properly sense glucose or secrete appropriate amounts of insulin.

Toward new therapies

This model also revealed steps along the glucose transport system where therapeutic intervention might help.

“We’re trying to understand what actually causes disease, which is defined as cellular dysfunction. Once we understand what causes disease we can make a difference by devising more rational and effective preventative and therapeutic approaches,” Marth said.

According to the American Diabetes Association, 8.3 percent of the U.S. population has diabetes. The disease can lead to nerve loss, blindness and death.


This research was funded by the Institute for Collaborative Biotechnologies (grant W911NF-09-0001 from the U.S. Army Research Office) and by the U.S. National Institutes of Health (National Institute of Diabetes and Digestive and Kidney Diseases grant DK048247 and National Institute of General Medical Sciences grant GM100192).

Original paper:

Luni, C., Marth, J., & Doyle, F. (2012). Computational Modeling of Glucose Transport in Pancreatic β-Cells Identifies Metabolic Thresholds and Therapeutic Targets in Diabetes PLoS ONE, 7 (12) DOI: 10.1371/journal.pone.0053130


Facebook Comments

About Author

Heather Buschman, Ph.D.

Heather was an SBP Communications staff member.



  1. Pingback: Type 2 diabetes: a cellular metabolism problem

Leave A Reply



* Copy This Password *

* Type Or Paste Password Here *

45,243 Spam Comments Blocked so far by Spam Free Wordpress