Coronary artery disease risk and lipidomic profiles are similar in familial and population-ascertained hyperlipidemias

2018 
Aims: To characterize and compare coronary artery disease (CAD) risk and detailed lipidomic profiles of individuals with familial and population-ascertained hyperlipidemias. Methods and Results: We determined incident CAD risk for 760 members of 66 hyperlipidemic families (≥ 2 first degree relatives with the same hyperlipidemia) and 19,644 Finnish FINRISK population study participants. We also quantified 151 lipid species in plasma or serum samples from 550 members of 73 hyperlipidemic pedigrees and 897 FINRISK participants using a mass spectrometric shotgun lipidomics platform. Hyperlipidemias (LDL-C or triacylglycerides over 90th population percentile) were associated with increased CAD risk (high LDL-C: HR 1.74, 95% CI 1.48-2.04; high triacylglycerides: HR 1.38, 95% CI 1.09-1.74) and the risk estimates were very similar between the family and population samples. High LDL-C was associated with altered levels of 105 lipid species in families (p-value range 0.033-7.3*10 -20 at 5% false discovery rate) and 51 species in the population samples (p-value range 0.017-6.8*10 -21 ). Hypertriglyceridemia was associated with altered levels of 117 lipid species in families (p-value range 0.035-1.8*10 -49 ) and 119 species in the population sample (p-value range 0.038-2.3*10 -56 ). The lipidomics profiles of hyperlipidemias were highly similar in families and population samples. Conclusion: We identified distinct lipidomic profiles associated with high LDL-C and triacylglyceride levels. CAD risk, lipidomic profiles and genetic profiles are highly similar between familial and population-ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms. Our results do not support different screening and treatment for such hyperlipidemias.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    42
    References
    1
    Citations
    NaN
    KQI
    []