Lipidomics Approach Developed to Predict Cardiovascular Disease, Diabetes

Current detection of cardiovascular disease and diabetes relies heavily on factors such as patient history, sex, age, body mass index, as well as blood panels measuring blood glucose and lipid metabolites, such as high- and low-density cholesterol and triglycerides.

Large population-based genotyping efforts undertaken during recent years have demonstrated that many phenotypes, including predisposition to human diseases, are polygenic, i.e., result from a large number of genetic loci, each having a small effect. In typical genome-wide association studies (GWAS), these effect sizes are estimated separately for each variant position because a joint estimation is computationally intractable.

Clinical scientists at the Lund University (Malmö, Sweden) collaborating with those at Lipotype GmbH (Dresden, Germany) assessed type 2 diabetes (T2D) and cardiovascular disease (CVD) risk for 4,067 participants in a large prospective study, the Malmö Diet and Cancer-Cardiovascular Cohort. Investigators collected information on patient lifestyle as well as blood plasma samples from healthy, middle-aged Swedish residents, who were first assessed from 1991 to 1994 and then clinically tracked until 2015.

Measurements (mmol/L) of fasting total cholesterol, HDL cholesterol, HbA1c, triglycerides, and glucose were obtained following standard procedure. Samples for lipid extraction for mass spectrometry lipidomics were analyzed by direct infusion in a QExactive mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA) equipped with a TriVersa NanoMate ion source (Advion Biosciences, Ithaca, NY, USA). Genotyping of participants was performed using the Illumina GSA v1 genotyping array (Illumina, San Diego, CA, USA).

The investigators found that patients at the highest risk for each disease had a 37% probability of acquiring type 2 diabetes and 40.5% chance of acquiring cardiovascular disease. The study participants in the high-risk group showed significantly altered lipidome compositions affecting 167 lipid species for type 2 diabetes and 157 lipid species for cardiovascular disease. Risk stratification was further improved by adding standard clinical variables to the model, resulting in a case rate of 51.0% and 53.3% in the highest risk group for T2D and CVD, respectively.

Chris Lauber, PhD, a professor and corresponding author for the study, said, “In principle, this study can be used to calculate the individual risk for T2D or CVD from the lipidome of a person. It is a first step in the direction of personalized medical practices, and now we want to move from research towards an assay that can be used in medical practice.”

The authors concluded that their results demonstrated that a subset of individuals at high risk for developing T2D or CVD can be identified years before disease incidence. The lipidomic risk, that 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. The study was originally published on March 3, 2022 in the journal PLOS Biology.

Related Links:
Lund University 
Lipotype GmbH 
Thermo Fisher Scientific 
Advion Biosciences 
Illumina 

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