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Researchers Develop Lipidomics Approach to Predict Cardiovascular Disease, Diabetes


NEW YORK ─ Researchers at Dresden, Germany-based Lipotype and Lund University in Sweden have developed an approach to simultaneously measure lipid concentrations in blood to predict the risk of developing cardiovascular disease and type 2 diabetes that they believe could expand the availability of tools for early disease detection.

The researchers recently published the results of a study in PLOS Biology, saying their lipidomics-based approach accurately predicted type 2 diabetes (T2D) and cardiovascular disease (CVD) up to 23 years in advance of patients developing the medical conditions.

The approach leveraged mass spectrometry and advanced data analytics to measure and analyze 184 lipid species.

Though much work is needed to implement such an approach to predict the onset of disease in the clinic, the study researchers said they believe broad lipid panels can eventually be developed to expand the range of tools for the early detection of T2D, CVD, and other medical conditions.

"In principle, this study can be used to calculate the individual risk for T2D or CVD from the lipidome of a person," said Chris Lauber, the corresponding author for the study and a professor at the Twincore Centre for Experimental and Clinical Infection Research.

"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," said Lauber, who was previously a researcher at Lipotype.

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. However, blood and other biological samples such as cerebrospinal fluid, skin, and tissue have many classes of lipids that, taken together, can be predictive of disease, Lipotype Chief Marketing Officer Henri Deda said in an interview.

"With a few thousand lipid molecules relevant to human health and disease," Lipotype researchers are also exploring the development of risk profiles that may be correlated with lipid metabolism changes to detect cancers and neurodegenerative diseases, Deda added.

In the recent study, the firm assessed type 2 diabetes and cardiovascular disease 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.

Using a subset of the blood samples and study data, the researchers developed lipid risk profiles for type 2 diabetes and cardiovascular disease by detecting and analyzing lipid concentrations using high-throughput, quantitative mass spectrometry. To develop the lipid-based risk profile, the authors performed repeated training and test rounds on the data, using two-thirds of lipid data to create a risk model and then seeing if the model accurately predicted risk in the remaining third of the data.

The investigators found that patients at the highest risk for each disease had a 37 percent probability of acquiring type 2 diabetes and 40.5 percent chance of acquiring cardiovascular disease. The researchers said 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.

According to Deda, the recent study showing the risk for disease onset as a result of the lipidomics analysis supports a broader trend to develop lipidomics approaches for the prognosis of disease and demonstrates that the approach could lead to long-term preventive measures and therapies.

Nonetheless, the use of lipidomics for clinical diagnostic applications would require a number of improvements including better comparability of results between laboratories for specific lipid profiles, said Olga Vvedenskaya, a researcher at the Max Planck Institute of Molecular Cell Biology and Genetics.

In general, lipidomics profiles such as those developed by Lipotype "are moving closer to clinical applications," said Vvedenskaya, who is an author of a recent study on clinical lipidomics published in the Journal of Mass Spectrometry and Advances in the Clinical Lab.

"In recent decades mass spectrometry-based workflows have become more technically robust and user-friendly, paving the way for adoption by routine clinical laboratories and, hence, potentially substantially expanding the number of lipids used in diagnostics beyond cholesterol and triacylglycerols," the researchers wrote, adding, however, that "to successfully evolve from the current research-grade methods to assays suitable for routine clinical applications, a harmonization — if not standardization — of these mass spectrometry-based workflows is necessary."

Introducing lipidomics for routine clinical testing would also require an increase in mass spectrometry adoption, Vvedenskaya said, adding that "many more mass spec labs would need to be introduced, which comes with the cost of education and training as well as the need to purchase instruments."

Additionally, unlike the use of single markers of cardiovascular disease and diabetes in current blood panels, combinations of different classes of "lipids are not so easy to measure and analyze," Vvedenskaya said, adding, "To introduce this to clinics, we need to measure how much of the various classes of lipids are in a sample and compare those measurements with established standards used by all labs."

Many research groups are working to move lipidomics toward the clinic, she noted, but for the practice to make a difference, patients will need to comply with advice stemming from lipidomics testing.

"This is a predictive analysis, so we can in principle tell patients that there is a certain probability they will develop a specific disease," Vvedenskaya said. "It is then up to patients to adjust their lifestyles, take certain medications, or do what is needed to reduce the risk of getting the disease."

Other research groups are also using lipids to develop disease risk scores.

For example, in January 2020, an international team of researchers, writing in the European Heart Journal, reported the development of a ceramide- and phospholipid-based risk score that can predict residual cardiovascular disease event risk in patients with coronary artery disease.

And last January, Australian researchers reported that plasma lipids have the potential to improve the detection and prediction of atrial fibrillation in patients with diabetes.

Though Lipotype believes lipidomics has significant potential for future application in clinical diagnostics, it currently serves researchers, and it is not disclosing whether it has plans to develop clinical tests, Deda said.

Nonetheless, lipidomics enabled by mass spec has the potential for affordable, high-throughput testing at high volumes, according to Deda. For large research studies, Lipotype charges less than €150 ($163) per sample, and in routine clinical use such testing should be far cheaper due to economies of scale, he added. The mass spectrometer used in its laboratory can analyze a few thousand samples per week, Deda said.