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October 18, 2016
Improving blood sugar estimates
At a Glance
- Researchers developed a formula to calculate average blood sugar levels more accurately than the standard method.
- The findings could lead to improved medical care for patients with diabetes.
Diabetes occurs when your blood glucose, or blood sugar, is too high. Over time, having too much glucose in your blood can cause health problems, such as heart disease, nerve damage, eye disorders, and kidney disease. The primary test used to estimate glucose levels for diabetes management is called the A1C test.
The A1C test measures the amount of glucose attached to hemoglobin, the protein in red blood cells that carries oxygen. Red blood cells are constantly forming and dying. They typically live for about 3 months. Thus, A1C results provide an estimate of a person’s average blood glucose levels over the past 3 months. However, levels of hemoglobin with glucose attached (glycated hemoglobin) can fluctuate depending on factors other than blood glucose, making A1C testing somewhat inaccurate.
To improve the accuracy of blood sugar estimates, a team led by Dr. John Higgins at Harvard Medical School and Massachusetts General Hospital investigated individual biological differences that may affect A1C results. The research was funded in part by NIH’s National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and an NIH Director’s New Innovator Award. Results were published in Science Translation Medicine on October 5, 2016.
The researchers analyzed data from their own hospital as well as from 3 previously published studies to assess how well the amount of glucose attached to hemoglobin reflects patients’ actual blood glucose levels. They found that the correlation was somewhat different for each patient. Using mathematical modeling, the team investigated biological differences that might contribute to the data’s variation.
Red blood cell turnover can occur on slightly different timescales for each person. Older red blood cells have more time to accumulate glycated hemoglobin than newer red blood cells. Differences in the average age of red blood cells for each patient, the researchers found, accounted for all of the variation seen between levels of glycated hemoglobin and blood glucose.
To personalize the model’s estimates, the team acquired data for more than 200 patients from 4 independent studies. The researchers determined the average red blood cell age for each person based on the relationship between continuous glucose measurements—taken using a tiny sensor inserted under the skin—and glycated hemoglobin measurements taken from a blood test. Using this information in the model, each patient’s average blood glucose levels could be calculated based on A1C tests with higher accuracy than the current standard method, reducing estimation errors by more than 50%.
“What we currently deem the gold standard for estimating average blood glucose is nowhere as precise as it should be,” says Higgins. “Our study not only pinpoints the root of the inaccuracy but also offers a way to get around it.”
More research is needed to determine how long continuous glucose measurements need to be taken to give the most precise results using this model.
―Tianna Hicklin, Ph.D.
- Diabetes in the U.S. Population
- Diabetes Prevention A Good Investment
- Blood Test May Predict Diabetes Risk
- Preventing Type 2 Diabetes: Steps Toward a Healthier Life
- Diabetes HealthSense
References: Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring. Malka R, Nathan DM, Higgins JM. Sci Transl Med. 2016 Oct 5;8(359):359ra130. PMID: 27708063.
Funding: NIH’s National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH Director’s New Innovator Award, and Abbott Diagnostics.