Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake

Abstract

Background: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants.Objective: The objective of the study was to identify common genetic variants that are associated with macronutrient intake.Design: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10−6 were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data.Results: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10−8) and lower fat (β ± SE: −0.21 ± 0.04%; P = 1.57 × 10−9) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)–increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10−10), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10−7).Conclusion: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

A common allele in FGF21 associated with preference for sugar consumption lowers body fat in the lower body and increases blood pressure

“…Whilst there is no direct evidence for the function of the rs838133 variant (or one in strong linkage disequilibrium), the A allele is very likely to represent a loss of FGF21 function, because it is very robustly associated with higher sugar and alcohol preference in people, a finding that is completely consistent with the genetic and pharmacological effects of FGF21 lowering in animal models, including non-human primates [1,2]. The apparently paradoxical association between the FGF21 A allele and higher circulating levels of FGF21 protein [12,14], may be caused by a feedback process that results in greater FGF21 production as a response to higher carbohydrate intake.…”

“…Whilst there is no direct evidence for the function of the rs838133 variant (or one in strong linkage disequilibrium), the A allele is very likely to represent a loss of FGF21 function, because it is very robustly associated with higher sugar and alcohol preference in people, a finding that is completely consistent with the genetic and pharmacological effects of FGF21 lowering in animal models, including non-human primates [1,2]. The apparently paradoxical association between the FGF21 A allele and higher circulating levels of FGF21 protein [12,14], may be caused by a feedback process that results in greater FGF21 production as a response to higher carbohydrate intake.The developers of therapies targeting FGF21 will be interested in the genotype-phenotype associations of the putative loss of function allele with a) higher percentage carbohydrate intake, b) higher alcohol intake, c) lower body fat percentage, d) altered body fat distribution, e) higher blood pressure, f) higher albumin to creatine ratio in the urine, g) higher LDL-cholesterol, h) higher triglycerides, but i) minimal if any effect on BMI and j) no evidence of an effect on type 2 diabetes or glycaemic traits. Of these associations, only that with higher percentage carbohydrate intake was convincingly shown before [13].…”

“…Studies in mice and non human primates show that genetically and pharmacologically raising FGF21 levels suppresses sugar and alcohol intake [1,2]. Three human genetic studies have shown that the minor A allele at rs838133 (A/G, Minor Allele Frequency=44.7%), which results in a synonymous change to the first exon of FGF21, is associated with higher carbohydrate and lower protein and fat intake, with no effect on total calorie intake [12][13][14]. Soberg et al showed that the carbohydrate preference was specific to sugary products, and may also increase alcohol intake [13].…”

Rola genu podatności na otyłość (FTO) w rozwoju otyłości — przegląd

“…Increased fat intake in risk allele carriers was reported earlier [43,55,56]. Tanaka et al performed recently a meta-analysis of macronutrient intake in populations of European descent and showed that rs1421085 variant was associated with higher protein intake independently of BMI [59]. Corresponding results were demonstrated by the Malmo Diet and Cancer Study, where a higher percentage of energy from protein in diet was observed for A-allele carriers [60].…”

Prenatal exposure to cigarette smoke interacts with OPRM1 to modulate dietary preference for fat

“…[6][7][8] Preference for fatty foods is a complex trait regulated by genetic and environmental factors, but only a few such factors have been identified in human populations. [9][10][11][12][13][14] These include the opioid receptor mu-1 gene (OPRM1) 13 and prenatal exposure to maternal cigarette smoking (PEMCS).…”