Lipid Profiling Can Predict the Risk of Diabetes and CVD Years Before Onset

The analysis of lipid profiling in the prediction of risk of developing type 2 diabetes and cardiovascular diseases can aid in recommending lifestyle changes and diet before the development of the diseases.

The increased risk of having type 2 diabetes (T2D) and cardiovascular disease (CVD) has been a significant concern in the health care sector worldwide. Also, it has been regularly reported by the World Health Organization (WHO) that cardiovascular diseases (CVDs) and diabetes mellitus are part of the ten major leading causes of death globally. Some changes, such as increased blood pressure, cholesterol, and blood sugar level, are usually apparent before the onset of these diseases. Therefore, early detection of individuals at increased risk of having this disease is essential in preventing the disease Incidence. Furthermore, these diseases can influence specific measures like lifestyle changes such as healthy diet and exercise. In addition, machine learning models can help predict the risk of having T2D and CVD. Other factors such as lipid level and blood sugar levels, particularly evaluation of gene variations, protein complements, and metabolome, which includes lipidome, may aid in identifying physiopathology pathways that might be different among patients. Longitudinal studies that evaluate the relationship between the plasma lipidome and the incidence of developing T2D or CVD have been reported. However, the comparisons with genetic, proteomics, or metabolomics-based risk prediction factors are not commonly evaluated. Few studies include risk prediction of developing T2D or CVD among large population-based cohorts with many prevalence records and long monitoring. In this study conducted by Lipotype research lead Chris Lauber and his colleagues, they reported that genetics lipidomics and standard medical examination could be used to evaluate early detection of the risk of having T2D and CVD, which can help in the recommendation of diet and lifestyle intervention before the development of the diseases.

The study aims to evaluate whether comprehensive measurement of blood lipids or lipidomics can help predict the likelihood of developing type 2 diabetes (T2D) and cardiovascular disease (CVD) decades before onset. The researcher gathered data and blood samples from about 4,000 healthy, middle-aged Swedish individuals; the first assessment was conducted between 1991 to 1994 and was monitored until 2015. Lipidomics, genetics, and medical assessment were integrated to examine the risk of developing T2D and CVD in the future. This analysis was carried out among 4,067 participants from a large prospective population-based cohort, the Malmö Diet and Cancer-Cardiovascular Cohort. A concentration of 184 lipids was examined using baseline blood samples with high throughput,  reproducible, and quantitative mass spectrometry. 13.8% and 22% of participants developed T2D and CVD during the follow-up period, respectively. To develop lipid profiling, the researchers conducted continuous test rounds on the data generated by using two-thirds of the randomly selected lipids data to establish the risk model and examine if the model can predict risk in the remaining third accurately. After developing this model, individuals were divided into six groups according to their lipids profile. In addition, several risk scores for CVD and T2D risk factors were evaluated and monitored for up to 23 years among participants. The measurement was performed at baseline when the participants were healthy using Ridge regression analysis. This score was used to distinguish participants into risk groups.

They reported that the lipidomics risk score obtained from the measurement of 184 plasma lipid concentrations showed 168% for the highest risk group of having T2D and 84% for the highest risk group of having CVD. There was a 77% reduction in the risk rate in the lowest risk category for T2D and a 53% reduction in the lowest risk category for CVD compared to the 13.8% and 22.0% of the average-case rate. The increment in the risk of developing these two diseases was not dependent on known genetic risk factors and years before the disease onset.

The results show that one can predict individuals at high risk for developing T2D or CVD years before the onset of the disease, which can help such people take adequate measures to prevent the onset of the disease. Also, Lipidomics,  genetics, and patient history may be used to investigate when and why the disease will occur; and the evaluation of the lipids that contributed to the highest risk can result in the identification of new drug therapy.

Practice Pearls:

• Type 2 diabetes (T2D) and cardiovascular disease (CVD) have been major global health concerns that can be prevented by diet and lifestyle modifications.
• Analysis of lipid profile can predict the risk of developing type 2 diabetes and cardiovascular diseases, which can help such individuals take adequate measures to prevent the disease’s development.
• Lipidomics can expand the toolkit for the early detection of people at increased risk of having T2D and cardiovascular diseases.

References for “Lipid Profiling Can Predict the Risk of Diabetes and CVD Years Before Onset”:
Lauber C, Gerl MJ, Klose C, Ottosson F, Melander O, Simons K. Lipidomic risk scores are independent of polygenic risk scores and can predict the incidence of diabetes and cardiovascular disease in a large population cohort. PLOS Biology. https://journals.plos.org/plosbiology/article?id=10.1371%2Fjournal.pbio.3001561.

Lipid profiling can predict the risk of diabetes cardiovascular disease decades before onset. ScienceDaily. https://www.sciencedaily.com/releases/2022/03/220303141145.htm. Published March 3, 2022.    

          Janet Falade, PharmD Candidate, South College School of Pharmacy