U.S. and Toronto General Research Institute scientists have identified a set of distinct compounds, or "fingerprints," in the blood, which accurately predict which women with gestational diabetes will develop type 2 diabetes.
Gestational diabetes is a transient form of diabetes which occurs in 3 per cent to 14 per cent of pregnant women. If not carefully managed, risks include developing complications in pregnancy and delivery such as early birth and respiratory distress syndrome.
Moreover, these women are more than seven times as likely to develop type 2 diabetes five to 10 years after pregnancy.
This makes it important to accurately predict which women are at highest risk so that early interventions can be developed for them. Additionally, the early treatment of diabetes can prevent or delay complications and reduce the risk of experiencing complications in subsequent pregnancies.
Dr. Michael Wheeler, Senior Scientist at Toronto General Research Institute, and Dr. Erica Gunderson, Senior Research Scientist with the Kaiser Permanente Northern California Division of Research, jointly used a technique called targeted metabolomics to simultaneously screen 182 different human metabolytes or compounds in the blood of birth mothers with gestational diabetes who go on to developtype 2 diabetes. Changes in some of these compounds occur before glucose levels rise, indicating higher risk earlier than conventional tests.
The metabolomics approach uses advanced computer learning techniques evolved from Artificial Intelligence to identify early diagnostic biomarkers or signatures of disease from large data sets that have the best predictive abilities for complex pathologies such as diabetes.
Diagnostic test could be possible
With a discriminative power of more than 83 per cent, the method predicted which women would develop type 2 diabetes later on, significantly better than 73 per cent for conventional glucose tests. Of the 182 metabolites measured in the blood samples, only a small subset of four metabolites were needed to accurately predict diabetes.
"Such a simple signature could quite easily be developed into a diagnostic test," says Dr. Wheeler, adding that this new method may also be able to predict who may develop type 2 diabetes in a much larger and diverse population.
This work is the first metabolomics study of who is more likely to transition from gestational diabetes to type 2 diabetes, above and beyond the risk contributed by obesity, often cited as the single best predictor of type 2 diabetes.
Metabolites – small molecules such as amino acids, sugars, fats, and others – are of interest to researchers because they can provide a more comprehensive understanding of how disease develops, and identify what types of profiles or metabolic "fingerprints" could help in assessing risk.
An individual's metabolic fingerprint –determined through a single blood sample – could, in the future, be used to predict the risk of disease or health status. Personalized recommendations could be based on these fingerprints, such as what specific medication, diet or exercise could prevent the onset of disease.
In recent research published in
Diabetes, Volume 65, 2016, Dr. Wheeler and U.S. researchers used mass spectrometry, an analytical technique which can measure multiple chemical components ina wide spectrum of molecules, to identify the subset of four metabolites that predict whether moms who had gestational diabetes develop diabetes.
Opportunity to study changes in compounds
High-throughput screening is powerful, says Dr. Wheeler, allowing us to quickly conduct thousands of chemical tests to rapidly identify the compounds important in the early stages of disease.
"This gives us the opportunity to study changes in compounds, or biochemical pathways, very efficiently, which helps us understand what is involved in the early onset of disease," he says.
Fasting blood samples were obtained from 1,035 women diagnosed with gestational diabetes in the Kaiser Permanente's Study of Women, Infant Feeding and Type 2 Diabetes after GDM Pregnancy, funded by the U.S. National Institutes of Health.
The samples were analyzed for levels of glucose and insulin, fats, and other compounds. Follow-up assessments occurred at two months after delivery and annually until two years for type 2 diabetes.
Drs. Wheeler and Gunderson are hoping to use this same method to screen men and women in the general population to see how well they can predict who will develop type 2 diabetes.
How is diabetes currently diagnosed?
A fasting blood or glucose tolerance test is usually used to diagnose diabetes. It measures blood glucose or sugar levels after about eight hours of fasting, with no food or liquids except water.
However, studies have shown that new mothers do experience barriers with follow-up diabetes testing, as a result of adjusting to a new baby, postpartum stressors and mood symptoms, such as anxiety and feeling overwhelmed, or the perception that they may not be at high risk for subsequent diabetes. Rates of follow-up for these moms can be as low as 16 per cent.
A single, non-fasting, and less time-consuming blood test which could be administered in the hospital could be helpful for these moms.
No such test is currently available.
