Dataset Information

Sex-specific genetic architecture in response to American and ketogenic diets.

ABSTRACT:

Background/objectives

There is a growing appreciation for individual responses to diet. In a previous study, mouse strain-specific responses to American and ketogenic diets were observed. In this study, we searched for genetic variants underlying differences in the responses to American and ketogenic diets between C57BL/6J (B6) and FVB/NJ (FVB) mouse strains.

Results

Genetic mapping of fat and lean mass gain revealed QTLs on Chromosome (Chr) 1 at 191.6 Mb (Fmgq1) (P < 0.001, CI = 180.2-194.4 Mb), Chr5 at 73.7 Mb (Fmgq2, Lmgq1) (P < 0.001, CI = 66.1-76.6 Mb), and Chr7 at 40.5 Mb (Fmgq3) (P < 0.01, CI = 36.6-44.5 Mb). Analysis of serum HDL cholesterol concentration identified a significant (P < 0.001, CI = 160.6-176.1 Mb) QTL on Chr1 at 168.6 Mb (Hdlq1). Causal network inference suggests that HDL cholesterol and fat mass gain are both linked to Fmgq1.

Conclusions

Strong sex effects were identified at both Fmgq2 and Lmgq1, which are also diet-dependent. Interestingly, Fmgq2 and Fmgq3 affect fat gain directly, while Fmgq1 influences fat gain directly and via an intermediate change in serum cholesterol. These results demonstrate how precision nutrition will be advanced through the integration of genetic variation and sex in physiological responses to diets varied in carbohydrate composition.

SUBMITTER: Salvador AC

PROVIDER: S-EPMC8159743 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe gut microbiota is modulated by a combination of diet, host genetics, and sex effects. The magnitude of these effects and interactions among them is important to understanding inter-individual variability in gut microbiota. In a previous study, mouse strain-specific responses to American and ketogenic diets were observed along with several QTLs for metabolic traits. In the current study, we searched for genetic variants underlying differences in the gut microbiota in response to American and ketogenic diets, which are high in fat and vary in carbohydrate composition, between C57BL/6 J (B6) and FVB/NJ (FVB) mouse strains.ResultsGenetic mapping of microbial features revealed 18 loci under the QTL model (i.e., marginal effects that are not specific to diet or sex), 12 loci under the QTL by diet model, and 1 locus under the QTL by sex model. Multiple metabolic and microbial features map to the distal part of Chr 1 and Chr 16 along with eigenvectors extracted from principal coordinate analysis of measures of β-diversity. Bilophila, Ruminiclostridium 9, and Rikenella (Chr 1) were identified as sex- and diet-independent QTL candidate keystone organisms, and Parabacteroides (Chr 16) was identified as a diet-specific, candidate keystone organism in confirmatory factor analyses of traits mapping to these regions. For many microbial features, irrespective of which QTL model was used, diet or the interaction between diet and a genotype were the strongest predictors of the abundance of each microbial trait. Sex, while important to the analyses, was not as strong of a predictor for microbial abundances.ConclusionsThese results demonstrate that sex, diet, and genetic background have different magnitudes of effects on inter-individual differences in gut microbiota. Therefore, Precision Nutrition through the integration of genetic variation, microbiota, and sex affecting microbiota variation will be important to predict response to diets varying in carbohydrate composition. Video Abstract.