scholarly journals Diet-gene interactions between dietary fat intake and common polymorphisms in determining lipid metabolism

2008 ◽  
Vol 60 (1) ◽  
Author(s):  
Dolores Corella
2020 ◽  
Vol 13 (6) ◽  
pp. 155-163
Author(s):  
Bridget A. Hannon ◽  
Caitlyn G. Edwards ◽  
Sharon V. Thompson ◽  
Sarah K. Burke ◽  
Nicholas A. Burd ◽  
...  

<b><i>Introduction:</i></b> The effect of various types of dietary fat on cardiometabolic health continues to be debated, due in part to the high heterogeneity of results following clinical trials investigating the effects of saturated (SFA) and unsaturated fat intake. This variability may be due to genetic differences. Individuals with obesity are at an increased risk for adverse cardiometabolic health and dyslipidemia, and often present with the combined phenotype of elevated triglyceride (TG) and decreased high-density lipoprotein (HDL) cholesterol concentrations. Studying genetic variants relevant to lipid and lipoprotein metabolism can elucidate the mechanisms by which diet might interact with genotype to influence these phenotypes. The objective of this study was to determine relationships of genetic variation, dietary fat intake, and blood lipid concentrations in adults with overweight and obesity. <b><i>Methods:</i></b> Genomic DNA, blood lipid concentrations (HDL and TG), and 7-day diet records were obtained from 101 adults (25–45 years of age) with overweight or obesity. Resting energy expenditure (REE) was measured using indirect calorimetry and used to determine implausible intakes using a modified Goldberg method (kilocalories/REE). Genetic variants included 23 single-nucleotide polymorphisms (SNPs) from 15 genes in lipid metabolism pathways. Variants were analyzed with dietary fat intake (total fat, SFA, monounsaturated fat [MUFA], and polyunsaturated fat [PUFA]) via regression analyses. All models were adjusted for age, sex, ancestry, visceral adipose tissue mass, and total kilocalorie intake. The Bonferroni correction was applied for multiple comparisons. <b><i>Results:</i></b> Two interactions were detected for TG concentrations. Five gene-diet interactions were associated with HDL concentrations. There was a significant interaction detected between the rs5882 variant of cholesterol-esterase transfer protein (<i>CETP</i>) and MUFA intake to associate with TG concentrations (interaction <i>p</i> = 0.004, <i>R</i><sup>2</sup> = 0.306). Among carriers of the <i>CETP-</i>rs5882 major allele (G), TG concentrations were significantly lower in individuals consuming more than the median MUFA intake (31 g/day) than in those with an intake below the median. Total dietary fat intake interacted with the rs13702 polymorphism of lipoprotein lipase (<i>LPL</i>) to associate with HDL concentrations (interaction <i>p</i> = 0.041, <i>R</i><sup>2</sup> = 0.419), by which individuals with the risk allele (G) had significantly higher HDL concentrations when consuming a higher-fat diet (&#x3e;92 g/day) than those with a lower-fat diet (56 ± 3 vs. 46 ± 2 mg/dL, <i>p</i> = 0.033). <b><i>Conclusions:</i></b> Interactions between dietary intake and genes in lipid metabolism pathways were found to be associated with blood lipid concentrations in adults with overweight and obesity. Fatty acid intake may not modulate blood lipid concentrations uniformly across all individuals. Additional research is needed to determine the biological causes of individual variability in response to dietary intake. Understanding the influence of nutrigenetic interactions on dyslipidemia can aid in the development and implementation of personalized dietary strategies to improve health.


2019 ◽  
Vol 8 (1) ◽  
pp. 199-213 ◽  
Author(s):  
Lianxin Peng ◽  
Qu Zhang ◽  
Yanhong Zhang ◽  
Zhendong Yao ◽  
Panpan Song ◽  
...  

2013 ◽  
Author(s):  
Eleanor B. Tate ◽  
Susan M. Schembre ◽  
Gillian O'Reilly ◽  
Mary Ann Pentz ◽  
Genevieve Dunton

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1893-P
Author(s):  
AMBER B. COURVILLE ◽  
SHANNA BERNSTEIN ◽  
MIRELLA GALVAN-DE LA CRUZ ◽  
ANTHONY ONUZURUIKE ◽  
NIRUPA R. MATTHAN ◽  
...  

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1734-P
Author(s):  
AUSTIN REILLY ◽  
SHIJUN YAN ◽  
ALEXA J. LONCHARICH ◽  
HONGXIA REN

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