• Lipid profiling can predict risk of diab

    From ScienceDaily@1:317/3 to All on Thu Mar 3 21:30:44 2022
    Lipid profiling can predict risk of diabetes, cardiovascular disease
    decades before onset
    Early testing may allow targeted interventions before disease develops


    Date:
    March 3, 2022
    Source:
    PLOS
    Summary:
    Simultaneous measurement of dozens of types of fats in the blood
    ('lipidomics') can predict the risk of developing type 2 diabetes
    (T2D) and cardiovascular disease (CVD) years in the future,
    according to a new study. Such early prediction through lipidomic
    profiling may provide the basis for recommending diet and lifestyle
    interventions before disease develops.



    FULL STORY ========================================================================== Simultaneous measurement of dozens of types of fats in the blood
    ("lipidomics") can predict the risk of developing type 2 diabetes (T2D)
    and cardiovascular disease (CVD) years in the future, according to a new
    study publishing March 3rd in the open-access journal PLOS Biology from
    Chris Lauber of Lipotype, Germany, and colleagues. Such early prediction through lipidomic profiling may provide the basis for recommending diet
    and lifestyle interventions before disease develops.


    ========================================================================== Current assessment of risk for T2D and CVD relies largely on patient
    history and current risk behaviors, and the levels and ratio of two major
    blood lipids, high- and low-density cholesterol. But the blood contains
    over one 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
    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
    T2D, and 22% developed CVD.

    To develop the lipid-based risk profile, the authors performed repeated training/test rounds on the data, using a randomly chosen two-thirds
    of lipid data to create a risk model, and then seeing if the model
    accurately predicts risk in the remaining third. Once the model was
    developed, individuals were clustered into one of six subgroups based
    on their lipidomics profile.

    Compared to the group averages, the risk for T2D 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.

    There are several potentially important implications of these
    findings. On an individual level, it may be possible to define risk
    decades before disease onset, possibly in time to take steps to avert
    disease. Lipidomics, either in combination with genetics and patient
    history or independent of them, may provide new insights into when and why disease begins. In addition, 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. In
    addition, 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.

    If that is true, Lauber said, "the lipidome may provide
    insights much beyond diabetes and cardiovascular disease
    risk." Lauber adds, "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." ========================================================================== Story Source: Materials provided by PLOS. Note: Content may be edited
    for style and length.


    ========================================================================== Journal Reference:
    1. Chris Lauber, Mathias J. Gerl, Christian Klose, Filip Ottosson, Olle
    Melander, Kai Simons. Lipidomic risk scores are independent of
    polygenic risk scores and can predict incidence of diabetes and
    cardiovascular disease in a large population cohort. PLOS Biology,
    2022; 20 (3): e3001561 DOI: 10.1371/journal.pbio.3001561 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2022/03/220303141145.htm

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