Biomarkers Identified for Type 2 Diabetes

Metabolites in the blood have been characterized that will provide insight into the pathological mechanisms of type 2 diabetes and in addition can be used as biomarkers to determine the disease risk.

A scientific team at the German Institute of Human Nutrition (Potsdam-Rehbruecke, Germany) and the Max Delbrueck Center for Molecular Medicine (Berlin, Germany) studied 4,000 blood samples. At the time the blood sample was taken, none of the study participants suffered from type 2 diabetes. However, during the average follow-up time of seven years, 891 participants were diagnosed with type 2 diabetes. There were 76 participants in the study who were already classified at the beginning of the study as individuals at high risk for type 2 diabetes, but at the time the blood sample was taken, they were still healthy.

Flow injection analysis tandem mass spectrometry was used to quantify 163 metabolites per blood sample, including acylcarnitines, amino acids, hexose, and phospholipids, in baseline serum samples. Serum hexose; phenylalanine; and diacyl-phosphatidylcholines C32:1, C36:1, C38:3, and C40:5 were independently associated with increased risk of type 2 diabetes. Serum glycine; sphingomyelin C16:1; acyl-alkyl-phosphatidylcholines C34:3, C40:6, C42:5, C44:4, and C44:5; and lysophosphatidylcholine C18:2 were associated with decreased risk.

The metabolites significantly improved type 2 diabetes prediction compared with established risk factors. They were further linked to insulin sensitivity and secretion in one study group and were partly replicated in the independent cohort. The data indicate that metabolic alterations, including sugar metabolites, amino acids, and choline-containing phospholipids, are associated early on with a higher risk of type 2 diabetes.

Tobias Pischon, MD MPH, the lead author, said “At the same time the metabolites can also be used as biomarkers to precisely determine the risk of diabetes at a very early stage, since the study is based on prospective data, which is data that were collected before the onset of the disease. The results of the new metabolomic analysis thus provide a good basis for developing new treatment and prevention methods." The study was published on October 4, 2012, in the journal Diabetes.

Related Links:
German Institute of Human Nutrition
Max Delbrueck Center for Molecular Medicine