medwireNews: Future risk for type 2 diabetes or cardiovascular disease (CVD) may be determined by a person’s lipid profile, suggests research published in PLOS Biology.
Chris Lauber (TWINCORE, Hanover, Germany) and co-authors say: “The lipidomic risk, which is derived from only one single mass spectrometric measurement that is cheap and fast, is informative and could extend traditional risk assessment based on clinical assays.”
Lauber and team determined the molar concentrations of 184 lipid species or subspecies in fasted blood plasma samples from 4067 participants of the prospective, population-based Malmö Diet and Cancer-Cardiovascular Cohort.
Using machine-learning methods, the researchers created a lipidomics risk score that stratified the participants into 10 risk groups.
They report that, during 23 years of follow-up, the incidence of type 2 diabetes in the lowest and highest deciles of risk was 3.2% and 37.0%, respectively. By comparison, the overall incidence was 13.8%.
Therefore, individuals in the lowest lipidomic risk decile had a 76.8% lower than average diabetes incidence while those in the highest risk decile had a 168.1% higher than average incidence, with corresponding odds ratios (ORs) of 0.21 and 3.67.
The team identified 167 lipid species that were significantly altered in the highest risk group relative to any of the other nine groups. These included elevated triglyceride and diglyceride levels and decreased phosphatidylcholine-O levels.
Lauber et al then investigated the impact of polygenic risk on the lipidomic model and observed that although polygenic risk marginally improved risk stratification, there was only limited correlation between the two scores.
This indicates “that the lipidome and genetic variants may constitute largely independent risk factors” for type 2 diabetes, the authors remark.
They add that this may be because the lipidome ”is a phenotypic measure that is influenced by lifestyle” and changes with time, which “could limit predictive power.”
When the researchers added clinical variables such as BMI, blood pressure, fasting plasma glucose, glycated hemoglobin, and cholesterol levels to lipidomic and polygenic risk, they found that stratification improved further, mainly as a result of the glucose measures. In this combined model, diabetes incidence was 1.1% in the lowest risk decile and 51.0% in the highest decile. The ORs relative to overall incidence were 0.07 and 6.12 in the lowest and highest deciles, respectively.
The investigators also applied their model to CVD risk and observed “striking similarities between the high-risk CVD and [type 2 diabetes] signatures.” For CVD, the ORs relative to overall incidence were 0.41 and 2.41 in the lowest and highest deciles, respectively
Lauber and colleagues conclude that their “results show that pathological alterations of the lipidome may arise years before a disease is diagnosed, therefore offering new opportunities for early risk assessment.”
medwireNews is an independent medical news service provided by Springer Healthcare Ltd. © 2022 Springer Healthcare Ltd, part of the Springer Nature Group