Simultaneous measurement of dozens of types of fats in the blood – lipidomics – can predict the risk of developing type 2 diabetes (T2DM) and cardiovascular disease (CVD) years in the future, according to a new study by Chris Lauber, and colleagues, at Lipotype in Dresden, Germany. Early prediction through lipidomic profiling may provide the basis for recommending diet and lifestyle interventions before disease develops according to the research published in open-access journal PLOS Biology.
Current assessment of risk for T2DM and CVD relies largely on patient history and current risk behaviours, and the levels, and ratio, of high- and low-density cholesterol. But the blood contains more than a hundred other types of lipids, which are thought to reflect at least in part aspects of metabolism and homeostasis throughout the body.
To assess whether a more comprehensive measure of blood lipids could increase the accuracy of risk prediction, the authors drew on data and blood samples from a longitudinal health study of over 4,000 healthy, middle-aged Swedish residents, first assessed from 1991 to 1994, and then followed until 2015. Using baseline blood samples, the concentrations of 184 lipids were assessed with high-throughput, quantitative mass spectrometry. During the follow-up period, 13.8% of participants developed T2DM, and 22% developed CVD.
Compared to the group averages, the risk for T2DM in the highest-risk group was 37%, an increase in risk of 168%. The risk for CVD in the highest-risk group was 40.5%, an increase in risk of 84%. Significant reductions in risk compared to the averages were also seen in the lowest-risk groups. The increased risk for either disease was independent of known genetic risk factors, and independent of the number of years until disease onset.
These findings show that on an individual level, it may be possible to define risks decades before onset. Lipidomics, either in combination with genetics and patient history or independent of them, may provide new insights into when and why disease begins. Additionally, by identifying those lipids that contribute most to risk, it may be possible to identify new drug candidates.
“The lipidomic risk, which is derived from only one single mass-spectrometric measurement that is cheap and fast, could extend traditional risk assessment based on clinical assay,” Lauber said.
If individual lipids in blood may be the consequences of, or contribute to, a wide variety of metabolic processes, which may be individually significant as markers of those processes.
“Strengthening disease prevention is a global joint effort with many facets. We show how lipidomics can expand our toolkit for early detection of individuals at high risk of developing diabetes and cardiovascular diseases,” Lauber concluded.