👤 Charles Desmarchelier

Lutein (L) and zeaxanthin (Z) are involved in visual function and could prevent age-related macular degeneration and chronic diseases and improve cognitive performances. Adipose tissue is the main storage site for these xanthophylls (Xanth). The factors affecting their concentrations in this tissue remain poorly understood but in animal models, genetic variations in apolipoprotein E and β-carotene oxygenase 2 have been associated with adipose tissue L concentration. Therefore, the aims of this study were to better characterize the interindividual variability of adipose tissue Xanth concentration and to identify single nucleotide polymorphisms (SNPs) associated with it. Periumbilical subcutaneous adipose tissue samples were collected on 6 occasions in 42 healthy adult males and L and Z concentrations were measured by HPLC. Participants had their whole genome genotyped and the associations of 3589 SNPs in 49 candidate genes with the concentrations of L and Z were measured. Mean L and Z concentrations were 281 ± 27 and 150 ± 14 nmol g Show less

Phytofluene is a colorless carotenoid with potential health benefits that displays a higher bioavailability compared to carotenoids such as lutein, β-carotene or lycopene. Several studies suggest its bioavailability displays an elevated interindividual variability. The aim of this work is to investigate whether a combination of SNPs is associated with this variability. Thirty-seven healthy adult males consume a test meal that provides phytofluene from a tomato puree. Phytofluene concentrations are measured at fast and in chylomicrons at regular time intervals after meal intake. Identification of the combination of SNPs that best explained the interindividual variability of the phytofluene response is assessed by partial least squares regression. There is a large interindividual variability in the phytofluene response, with CV = 88%. Phytofluene bioavailability is positively correlated with fasting plasma phytofluene concentration (r = 0.57; p = 2 × 10 This study reports a combination of SNPs that is associated with a significant part of the interindividual variability of phytofluene bioavailability in a healthy male adult population. Show less

The number of nutrigenetic studies dedicated to the identification of single nucleotide polymorphisms (SNPs) modulating blood lipid profiles in response to dietary interventions has increased considerably over the last decade. However, the robustness of the evidence-based science supporting the area remains to be evaluated. The objective of this review was to present recent findings concerning the effects of interactions between SNPs in genes involved in cholesterol metabolism and transport, and dietary intakes or interventions on circulating cholesterol concentrations, which are causally involved in cardiovascular diseases and established biomarkers of cardiovascular health. We identified recent studies (2014-2020) that reported significant SNP-diet interactions in 14 cholesterol-related genes ( Show less

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. We aimed to identify a combination of SNPs associated with the postprandial CM TG response. 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. 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. Using a multivariate approach, we report a combination of SNPs that explains a significant part of the variability in the postprandial CM TG response. Show less