Quantitative trait loci affecting liver fat content in mice

Genetic control of obesity, glucose homeostasis, dyslipidemia and fatty liver in a mouse model of diet-induced metabolic syndrome

BACKGROUND/OBJECTIVES

Both genetic and dietary factors contribute to the metabolic syndrome (MetS) in humans and animal models. Characterizing their individual roles as well as relationships among these factors is critical for understanding MetS pathogenesis and developing effective therapies. By studying phenotypic responsiveness to high-risk versus control diet in two inbred mouse strains and their derivatives, we estimated the relative contributions of diet and genetic background to MetS, characterized strain-specific combinations of MetS conditions, and tested genetic and phenotypic complexity on a single substituted chromosome.

METHODS

Ten measures of metabolic health were assessed in susceptible C57BL/6 J and resistant A/J male mice fed either a control or a high-fat, high-sucrose (HFHS) diet, permitting estimates of the relative influences of strain, diet and strain-diet interactions for each trait. The same traits were measured in a panel of C57BL/6 J (B6)-Chr(A/J) chromosome substitution strains (CSSs) fed the HFHS diet, followed by characterization of interstrain relationships, covariation among metabolic traits and quantitative trait loci (QTLs) on Chromosome 10.

RESULTS

We identified significant genetic contributions to nine of ten metabolic traits and significant dietary influence on eight. Significant strain-diet interaction effects were detected for four traits. Although a range of HFHS-induced phenotypes were observed among the CSSs, significant associations were detected among all traits but one. Strains were grouped into three clusters based on overall phenotype and specific CSSs were identified with distinct and reproducible trait combinations. Finally, several Chr10 regions were shown to control the severity of MetS conditions.

CONCLUSIONS

Generally strong genetic and dietary effects validate these CSSs as a multifactorial model of MetS. Although traits tended to segregate together, considerable phenotypic heterogeneity suggests that underlying genetic factors influence their co-occurrence and severity. Identification of multiple QTLs within and among strains highlights both the complexity of genetically regulated, diet-induced MetS and the ability of CSSs to prioritize candidate loci for mechanistic studies.

The genetic architecture of NAFLD among inbred strains of mice

To identify genetic and environmental factors contributing to the pathogenesis of non-alcoholic fatty liver disease, we examined liver steatosis and related clinical and molecular traits in more than 100 unique inbred mouse strains, which were fed a diet rich in fat and carbohydrates. A >30-fold variation in hepatic TG accumulation was observed among the strains. Genome-wide association studies revealed three loci associated with hepatic TG accumulation. Utilizing transcriptomic data from the liver and adipose tissue, we identified several high-confidence candidate genes for hepatic steatosis, including Gde1, a glycerophosphodiester phosphodiesterase not previously implicated in triglyceride metabolism. We confirmed the role of Gde1 by in vivo hepatic over-expression and shRNA knockdown studies. We hypothesize that Gde1 expression increases TG production by contributing to the production of glycerol-3-phosphate. Our multi-level data, including transcript levels, metabolite levels, and gut microbiota composition, provide a framework for understanding genetic and environmental interactions underlying hepatic steatosis.

Identification of eQTLs for hepatic Xbp1s and Socs3 gene expression in mice fed a high-fat, high-caloric diet

Nonalcoholic fatty liver disease (NAFLD) is a highly prevalent form of human hepatic disease and feeding mice a high-fat, high-caloric (HFHC) diet is a standard model of NAFLD. To better understand the genetic basis of NAFLD, we conducted an expression quantitative trait locus (eQTL) analysis of mice fed a HFHC diet. Two-hundred sixty-five (A/J × C57BL/6J) F₂ male mice were fed a HFHC diet for 8 wk. eQTL analysis was utilized to identify genomic regions that regulate hepatic gene expression of Xbp1s and Socs3. We identified two overlapping loci for Xbp1s and Socs3 on Chr 1 (164.0–185.4 Mb and 174.4–190.5 Mb, respectively) and Chr 11 (41.1–73.1 Mb and 44.0–68.6 Mb, respectively), and an additional locus for Socs3 on Chr 12 (109.9–117.4 Mb). C57BL/6J-Chr 11^A/J/ NaJ mice fed a HFHC diet manifested the A/J phenotype of increased Xbp1s and Socs3 gene expression (P < 0.05), whereas C57BL/6J-Chr 1^A/J/ NaJ mice retained the C57BL/6J phenotype. In addition, we replicated the eQTLs on Chr 1 and Chr 12 (LOD scores ≥3.5) using mice from the BXD murine reference panel challenged with CCl₄ to induce chronic liver injury and fibrosis. We have identified overlapping eQTLs for Xbp1 and Socs3 on Chr 1 and Chr 11, and consomic mice confirmed that replacing the C57BL/6J Chr 11 with the A/J Chr 11 resulted in an A/J phenotype for Xbp1 and Socs3 gene expression. Identification of the genes for these eQTLs will lead to a better understanding of the genetic factors responsible for NAFLD and potentially other hepatic diseases.

The effect of dietary fat intake on hepatic gene expression in LG/J AND SM/J mice

Background

The liver plays a major role in regulating metabolic homeostasis and is vital for nutrient metabolism. Identifying the genetic factors regulating these processes could lead to a greater understanding of how liver function responds to a high-fat diet and how that response may influence susceptibilities to obesity and metabolic syndrome. In this study we examine differences in hepatic gene expression between the LG/J and SM/J inbred mouse strains and how gene expression in these strains is affected by high-fat diet. LG/J and SM/J are known to differ in their responses to a high-fat diet for a variety of obesity- and diabetes-related traits, with the SM/J strain exhibiting a stronger phenotypic response to diet.

Results

Dietary intake had a significant effect on gene expression in both inbred lines. Genes up-regulated by a high-fat diet were involved in biological processes such as lipid and carbohydrate metabolism; protein and amino acid metabolic processes were down regulated on a high-fat diet. A total of 259 unique transcripts exhibited a significant diet-by-strain interaction. These genes tended to be associated with immune function. In addition, genes involved in biochemical processes related to non-alcoholic fatty liver disease (NAFLD) manifested different responses to diet between the two strains. For most of these genes, SM/J had a stronger response to the high-fat diet than LG/J.

Conclusions

These data show that dietary fat impacts gene expression levels in SM/J relative to LG/J, with SM/J exhibiting a stronger response. This supports previous data showing that SM/J has a stronger phenotypic response to high-fat diet. Based upon these findings, we suggest that SM/J and its cross with the LG/J strain provide a good model for examining non-alcoholic fatty liver disease and its role in metabolic syndrome.

Genetic effects at pleiotropic loci are context-dependent with consequences for the maintenance of genetic variation in populations

Context-dependent genetic effects, including genotype-by-environment and genotype-by-sex interactions, are a potential mechanism by which genetic variation of complex traits is maintained in populations. Pleiotropic genetic effects are also thought to play an important role in evolution, reflecting functional and developmental relationships among traits. We examine context-dependent genetic effects at pleiotropic loci associated with normal variation in multiple metabolic syndrome (MetS) components (obesity, dyslipidemia, and diabetes-related traits). MetS prevalence is increasing in Western societies and, while environmental in origin, presents substantial variation in individual response. We identify 23 pleiotropic MetS quantitative trait loci (QTL) in an F₁₆ advanced intercross between the LG/J and SM/J inbred mouse strains (Wustl:LG,SM-G16; n = 1002). Half of each family was fed a high-fat diet and half fed a low-fat diet; and additive, dominance, and parent-of-origin imprinting genotypic effects were examined in animals partitioned into sex, diet, and sex-by-diet cohorts. We examine the context-dependency of the underlying additive, dominance, and imprinting genetic effects of the traits associated with these pleiotropic QTL. Further, we examine sequence polymorphisms (SNPs) between LG/J and SM/J as well as differential expression of positional candidate genes in these regions. We show that genetic associations are different in different sex, diet, and sex-by-diet settings. We also show that over- or underdominance and ecological cross-over interactions for single phenotypes may not be common, however multidimensional synthetic phenotypes at loci with pleiotropic effects can produce situations that favor the maintenance of genetic variation in populations. Our findings have important implications for evolution and the notion of personalized medicine.

We look at gene-by-diet and gene-by-sex interactions underlying natural variation in multiple metabolic traits mapping to the same regions of the genome in a mouse model. We find that the underlying genetic architecture of these traits is different in different sex and diet contexts. We further use expression data and whole-genome polymorphism data to identify compelling candidates for experimental follow-up. We use these results to examine theoretical evolutionary predictions about how variation in populations can be maintained. There has been much discussion of late on how to use evolutionary theory to inform medical genomics. Mouse models may be especially appropriate for bridging the divide between evolutionary and biomedical research, because they allow the study of the effects of natural alleles on normal variation and because human-mouse homology is well defined. Our study is unique in examining quantitative trait loci from both evolutionary and biomedical perspectives, and we highlight the complex connections of the traits comprising the metabolic syndrome and the evolutionary implications of their underlying genetic architecture. This is important for understanding disease etiology and is relevant to personalized medicine.