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Metabolic profiling of MRI-measured liver fat in the UK Biobank.
Obesity 2023 March 6
OBJECTIVE: Liver fat associates with obesity-related metabolic disturbances and may precede incident diseases. Metabolomic profiles of liver fat in the UK Biobank were investigated.
METHODS: Regression models assessed the associations between 180 metabolites and proton density liver fat fraction (PDFF) measured 5 years later through magnetic resonance imaging, as the difference (in SD units) of each log metabolite measure with 1-SD higher PDFF among those without chronic disease and not taking statins, and by diabetes and cardiovascular diseases.
RESULTS: After accounting for confounders, multiple metabolites were associated positively with liver fat (p < 0.0001 for 152 traits), particularly extremely large and very large lipoprotein particle concentrations, very low-density lipoprotein triglycerides, small high-density lipoprotein particles, glycoprotein acetyls, monounsaturated and saturated fatty acids, and amino acids. Extremely large and large high-density lipoprotein concentrations had strong inverse associations with liver fat. Associations were broadly comparable among those with versus without vascular metabolic conditions, although negative, rather than positive, associations were observed between intermediate-density and large low-density lipoprotein particles among those with BMI ≥25 kg/m2 , diabetes, or cardiovascular diseases. Metabolite principal components showed a 15% significant improvement in risk prediction for PDFF relative to BMI, which was twice as great (but nonsignificant) compared with conventional high-density lipoprotein cholesterol and triglycerides.
CONCLUSIONS: Hazardous metabolomic profiles are associated with ectopic hepatic fat and are relevant to risk of vascular-metabolic disease.
METHODS: Regression models assessed the associations between 180 metabolites and proton density liver fat fraction (PDFF) measured 5 years later through magnetic resonance imaging, as the difference (in SD units) of each log metabolite measure with 1-SD higher PDFF among those without chronic disease and not taking statins, and by diabetes and cardiovascular diseases.
RESULTS: After accounting for confounders, multiple metabolites were associated positively with liver fat (p < 0.0001 for 152 traits), particularly extremely large and very large lipoprotein particle concentrations, very low-density lipoprotein triglycerides, small high-density lipoprotein particles, glycoprotein acetyls, monounsaturated and saturated fatty acids, and amino acids. Extremely large and large high-density lipoprotein concentrations had strong inverse associations with liver fat. Associations were broadly comparable among those with versus without vascular metabolic conditions, although negative, rather than positive, associations were observed between intermediate-density and large low-density lipoprotein particles among those with BMI ≥25 kg/m2 , diabetes, or cardiovascular diseases. Metabolite principal components showed a 15% significant improvement in risk prediction for PDFF relative to BMI, which was twice as great (but nonsignificant) compared with conventional high-density lipoprotein cholesterol and triglycerides.
CONCLUSIONS: Hazardous metabolomic profiles are associated with ectopic hepatic fat and are relevant to risk of vascular-metabolic disease.
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