CONTEXT: The postprandial chylomicron (CM) triacylglycerol (TG) response to dietary fat, which is positively associated with atherosclerosis and cardiovascular disease risk, displays a high interindividual variability. This is assumed to be due, at least partly, to polymorphisms in genes involved in lipid metabolism. Existing studies have focused on single nucleotide polymorphisms (SNPs), resulting in only a low explained variability. OBJECTIVE: We aimed to identify a combination of SNPs associated with the postprandial CM TG response. PARTICIPANTS AND METHODS: Thirty-three healthy male volunteers were subjected to 4 standardized fat tolerance test meals (to correct for intraindividual variability) and genotyped using whole-genome microarrays. The plasma CM TG concentration was measured at regular interval times after each meal. The association of SNPs in or near candidate genes (126 genes representing 6225 SNPs) with the postprandial CM TG concentration (0-8 h areas under the curve averaged for the 4 test meals) was assessed by partial least squares regression, a multivariate statistical approach. RESULTS: Data obtained allowed us to generate a validated significant model (P = 1.3 × 10(-7)) that included 42 SNPs in 23 genes (ABCA1, APOA1, APOA5, APOB, BET1, CD36, COBLL1, ELOVL5, FRMD5, GPAM, INSIG2, IRS1, LDLR, LIPC, LPL, LYPLAL1, MC4R, NAT2, PARK2, SLC27A5, SLC27A6, TCF7L2, and ZNF664) and explained 88% of the variance. In 39 of these SNPs, univariate analysis showed that subjects with different genotypes exhibited significantly different (q < .05) postprandial CM TG responses. CONCLUSIONS: Using a multivariate approach, we report a combination of SNPs that explains a significant part of the variability in the postprandial CM TG response.
CONTEXT: The postprandial chylomicron (CM) triacylglycerol (TG) response to dietary fat, which is positively associated with atherosclerosis and cardiovascular disease risk, displays a high interindividual variability. This is assumed to be due, at least partly, to polymorphisms in genes involved in lipid metabolism. Existing studies have focused on single nucleotide polymorphisms (SNPs), resulting in only a low explained variability. OBJECTIVE: We aimed to identify a combination of SNPs associated with the postprandial CM TG response. PARTICIPANTS AND METHODS: Thirty-three healthy male volunteers were subjected to 4 standardized fat tolerance test meals (to correct for intraindividual variability) and genotyped using whole-genome microarrays. The plasma CM TG concentration was measured at regular interval times after each meal. The association of SNPs in or near candidate genes (126 genes representing 6225 SNPs) with the postprandial CM TG concentration (0-8 h areas under the curve averaged for the 4 test meals) was assessed by partial least squares regression, a multivariate statistical approach. RESULTS: Data obtained allowed us to generate a validated significant model (P = 1.3 × 10(-7)) that included 42 SNPs in 23 genes (ABCA1, APOA1, APOA5, APOB, BET1, CD36, COBLL1, ELOVL5, FRMD5, GPAM, INSIG2, IRS1, LDLR, LIPC, LPL, LYPLAL1, MC4R, NAT2, PARK2, SLC27A5, SLC27A6, TCF7L2, and ZNF664) and explained 88% of the variance. In 39 of these SNPs, univariate analysis showed that subjects with different genotypes exhibited significantly different (q < .05) postprandial CM TG responses. CONCLUSIONS: Using a multivariate approach, we report a combination of SNPs that explains a significant part of the variability in the postprandial CM TG response.
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