Analysing the levels of various metabolites in the blood can reveal the risk of type 2 diabetes up to 26 years before diagnosis. A researcher says that this gives scientists an unprecedented opportunity to see what is happening in the body decades before the disease develops – and understanding how this might be prevented much earlier.
Type 2 diabetes starts long before diagnosis. Researchers can now detect signs of the disease in blood samples up to 26 years before it is clinically identified.
A large new international study shows how hundreds of metabolites – small molecules in the blood that reflect the body’s metabolism – change long before the disease becomes visible in standard clinical measurements.
The results suggest that specific changes in these molecules act as early traces of a disease process that may be underway decades before diagnosis, opening the possibility of much earlier prevention.
Based on the analyses, the researchers identified a panel of 44 metabolites that best predict disease development.
When these 44 metabolites are combined with genetic profiles, dietary habits and other health data, researchers can build a far clearer picture of who is at risk of developing the disease – long before symptoms appear.
“The interaction between metabolites, genes, physical activity and diet creates a picture of disease risk. We can now tell people more precisely what their risk is and how they may change that risk profile through, for example, exercise and dietary changes,” explains a researcher behind the study, Marta Guasch Ferré, Associate Professor at the Department of Epidemiology of the University of Copenhagen, Denmark.
The research was published in Nature Medicine and is based on analysis of a large dataset of blood samples.
Hundreds of blood molecules reveal early signals of diabetes
To identify these early signals, the researchers analysed metabolites in blood samples from 23,634 people who did not have diabetes when the samples were taken. The participants were followed for up to 26 years, during which both disease development and other health data were recorded.
During this follow-up period, around 4,000 participants developed the disease – and their blood samples already showed early metabolic changes. Within the dataset, the algorithm identified clear metabolite patterns – chemical traces of the body’s metabolism – that were far more common for these individuals than among those who remained healthy, long before diagnosis.
The analysis included 469 metabolites, of which 235 were statistically associated with an increased risk of developing type 2 diabetes during the follow-up period.
Sixty-seven of these metabolites had not previously been linked to the risk of the disease.
Marta Guasch Ferré explains that metabolites are involved in many biological processes in the body, including regulating glucose metabolism, producing bile acids and other key metabolic signalling pathways.
Further genetic analysis linked these metabolites to biological signalling pathways known to have central roles in the disease, including insulin resistance, the regulation of glucose and insulin, fat storage, energy balance and liver function – providing independent support for the metabolic findings.
“We found that higher levels of some of these metabolites increase the risk of developing type 2 diabetes, whereas others appear to have a protective effect when present at higher levels. The interesting thing is that we can now measure these levels and identify risk decades before the disease occurs,” notes Marta Guasch Ferré.
A panel of 44 metabolites sharply improves risk prediction
Based on these results, the researchers developed a panel of 44 of the identified metabolites to test whether these signals could improve models used to predict the risk of developing type 2 diabetes.
Today, risk is typically assessed using traditional factors such as blood glucose levels, age, body-mass index and smoking status.
When the researchers added measurements of the 44 metabolites, the risk model became significantly more accurate and was able to identify individuals with a high risk of developing the disease decades before diagnosis.
“We have created a model that combines metabolites with genetic and clinical risk factors to improve risk prediction. The earlier we can identify people who are at high risk of developing type 2 diabetes, the earlier we can intervene and potentially prevent the disease from developing,” says Marta Guasch Ferré.
Metabolites reveal biological pathways behind diabetes
Although the results are promising, Marta Guasch Ferré acknowledges that a long time will likely elapse before metabolite analysis becomes part of routine risk assessment for patients.
Most doctors still rely on simpler measures such as blood glucose levels, body weight and medical history.
For that reason, metabolite analysis is unlikely to become part of the tests offered in general practice in the near future.
However, such analysis may become important in research investigating whether interventions can reduce the risk of developing the disease.
For this type of research, being able to identify individuals at particularly high risk as accurately as possible is crucial.
Metabolite studies may also provide valuable insights into the biological signalling pathways that drive the disease – and could therefore help to identify new treatment targets and potentially enable the disease to be prevented long before diagnosis.
