Genotype X diet interactions in mice predisposed to mammary cancer. I. Body weight and fat

Genotype-by-sex-by-diet interactions for nutritional preference, dietary consumption, and lipid deposition in a field cricket

Changes in feeding behaviour, especially the overconsumption of calories, has led to a rise in the rates of obesity, diabetes, and other associated disorders in humans and a range of animals inhabiting human-influenced environments. However, understanding the relative contribution of genes, the nutritional environment, and their interaction to dietary intake and lipid deposition in the sexes still remains a major challenge. By combining nutritional geometry with quantitative genetics, we determined the effect of genes, the nutritional environment, and their interaction on the total nutritional preference (TP), total diet eaten (TE), and lipid mass (LM) of male and female black field crickets (Teleogryllus commodus) fed one of four diet pairs (DPs) differing in the ratio of protein to carbohydrate and total nutritional content. We found abundant additive genetic variance for TP, TE, and LM in both sexes and across all four DPs, with significant genetic correlations between TE and TP and between TP and LM in males. We also found significant genotype-by-DP and genotype-by-sex-by-DP interactions for each trait and significant genotype-by-sex interactions for TE and LM. Complex interactions between genes, sex, and the nutritional environment, therefore, play an important role in nutrient regulation and lipid deposition in T. commodus. This finding may also help explain the increasing rate of obesity and the maintenance of sex differences in obesity observed across many animal species, including humans.

Effects of a standard high-fat diet with or without multiple deficiencies on bone parameters in ovariectomized mature rat

The aim of this study was to determine the effects of a standard high fat diet (D12451) with or without vitamin D3, phosphorus, and calcium (i.e., high-fat diet [HFD] or high-fat deficient diet [HFDD]) on the bone parameters of ovariectomized female rats. Six-month-old of female Sprauge Dawley (SD) rats were randomly divided into six study groups: sham operation with standard chow diet (SSCD), sham operation with a HFD (SHFD), sham operation with a HFDD (SHFDD), ovariectomized (OVX), OVX with a HFD (OVX-HFD), and OVX with a HFDD (OVX-HFDD). A bilateral ovariectomy was administered to the OVX, OVX-HFD, and OVX-HFDD rats, while the SSCD, SHFD, and SHFDD rats were only given a laparotomy. Multiple analyses concerning the glucose and insulin tolerance, structure, bone strength, bone matrix, and mineralization of the rats were conducted in order to produce a detailed characterization of the effects of a HFD and a HFDD on postmenopausal osteoporotic rats. Seven months of HFD and HFDD feeding resulted in obesity and insulin resistance in female SD rats. A standard HFD increased the bone calcium content and bone strength of OVX rats. Conversely, the serum N-mid osteocalcin (N-MID-OT) and tartrate-resistant acid phosphatase (TRAP) levels in the OVX-HFDD group were increased, accompanied by a clear decrease in the bone mineral density (BMD), bone mineral content (BMC), bone calcium and bone strength, as well as reduced osteocalcin expression. A HFDD weakened the activity of the osteoblasts while aggravating bone loss and decreasing bone strength in ovariectomized rats, which may be due to the calcium, phosphorus and vitamin D3 deficiencies in the diet.

Obesity and Cancer: An Angiogenic and Inflammatory Link

With the current epidemic of obesity, a large number of patients diagnosed with cancer are overweight or obese. Importantly, this excess body weight is associated with tumor progression and poor prognosis. The mechanisms for this worse outcome, however, remain poorly understood. We review here the epidemiological evidence for the association between obesity and cancer, and discuss potential mechanisms focusing on angiogenesis and inflammation. In particular, we will discuss how the dysfunctional angiogenesis and inflammation occurring in adipose tissue in obesity may promote tumor progression, resistance to chemotherapy, and targeted therapies such as anti-angiogenic and immune therapies. Better understanding of how obesity fuels tumor progression and therapy resistance is essential to improve the current standard of care and the clinical outcome of cancer patients. To this end, we will discuss how an anti-diabetic drug such as metformin can overcome these adverse effects of obesity on the progression and treatment resistance of tumors.

High-Fat, High-Calorie Diet Enhances Mammary Carcinogenesis and Local Inflammation in MMTV-PyMT Mouse Model of Breast Cancer

Epidemiological studies provide strong evidence that obesity and the associated adipose tissue inflammation are risk factors for breast cancer; however, the molecular mechanisms are poorly understood. We evaluated the effect of a high-fat/high-calorie diet on mammary carcinogenesis in the immunocompetent MMTV-PyMT murine model. Four-week old female mice (20/group) were randomized to receive either a high-fat (HF; 60% kcal as fat) or a low-fat (LF; 16% kcal) diet for eight weeks. Body weights were determined, and tumor volumes measured by ultrasound, each week. At necropsy, the tumors and abdominal visceral fat were weighed and plasma collected. The primary mammary tumors, adjacent mammary fat, and lungs were preserved for histological and immunohistochemical examination and quantification of infiltrating macrophages, crown-like structure (CLS) formation, and microvessel density. The body weight gains, visceral fat weights, the primary mammary tumor growth rates and terminal weights, were all significantly greater in the HF-fed mice. Adipose tissue inflammation in the HF group was indicated by hepatic steatosis, pronounced macrophage infiltration and CLS formation, and elevations in plasma monocyte chemoattractant protein-1 (MCP-1), leptin and proinflammatory cytokine concentrations. HF intake was also associated with higher tumor-associated microvascular density and the proangiogenic factor MCP-1. This study provides preclinical evidence in a spontaneous model of breast cancer that mammary adipose tissue inflammation induced by diet, enhances the recruitment of macrophages and increases tumor vascular density suggesting a role for obesity in creating a microenvironment favorable for angiogenesis in the progression of breast cancer.

Hidden genetic variation evolves with ecological specialization: the genetic basis of phenotypic plasticity in Arctic charr ecomorphs

The genetic variance that determines phenotypic variation can change across environments through developmental plasticity and in turn play a strong role in evolution. Induced changes in genotype-phenotype relationships should strongly influence adaptation by exposing different sets of heritable variation to selection under some conditions, while also hiding variation. Therefore, the heritable variation exposed or hidden from selection is likely to differ among habitats. We used ecomorphs from two divergent populations of Arctic charr (Salvelinus alpinus) to test the prediction that genotype-phenotype relationships would change in relation to environment. If present over several generations this should lead to divergence in genotype-phenotype relationships under common conditions, and to changes in the amount and type of hidden genetic variance that can evolve. We performed a common garden experiment whereby two ecomorphs from each of two Icelandic lakes were reared under conditions that mimicked benthic and limnetic prey to induce responses in craniofacial traits. Using microsatellite based genetic maps, we subsequently detected QTL related to these craniofacial traits. We found substantial changes in the number and type of QTL between diet treatments and evidence that novel diet treatments can in some cases provide a higher number of QTL. These findings suggest that selection on phenotypic variation, which is both genetically and environmentally determined, has shaped the genetic architecture of adaptive divergence in Arctic charr. However, while adaptive changes are occurring in the genome there also appears to be an accumulation of hidden genetic variation for loci not expressed in the contemporary environment.

Quantitative trait loci for energy balance traits in an advanced intercross line derived from mice divergently selected for heat loss

Obesity in human populations, currently a serious health concern, is considered to be the consequence of an energy imbalance in which more energy in calories is consumed than is expended. We used interval mapping techniques to investigate the genetic basis of a number of energy balance traits in an F₁₁ advanced intercross population of mice created from an original intercross of lines selected for increased and decreased heat loss. We uncovered a total of 137 quantitative trait loci (QTLs) for these traits at 41 unique sites on 18 of the 20 chromosomes in the mouse genome, with X-linked QTLs being most prevalent. Two QTLs were found for the selection target of heat loss, one on distal chromosome 1 and another on proximal chromosome 2. The number of QTLs affecting the various traits generally was consistent with previous estimates of heritabilities in the same population, with the most found for two bone mineral traits and the least for feed intake and several body composition traits. QTLs were generally additive in their effects, and some, especially those affecting the body weight traits, were sex-specific. Pleiotropy was extensive within trait groups (body weights, adiposity and organ weight traits, bone traits) and especially between body composition traits adjusted and not adjusted for body weight at sacrifice. Nine QTLs were found for one or more of the adiposity traits, five of which appeared to be unique. The confidence intervals among all QTLs averaged 13.3 Mb, much smaller than usually observed in an F₂ cross, and in some cases this allowed us to make reasonable inferences about candidate genes underlying these QTLs. This study combined QTL mapping with genetic parameter analysis in a large segregating population, and has advanced our understanding of the genetic architecture of complex traits related to obesity.

Interleukin-18 null mutation increases weight and food intake and reduces energy expenditure and lipid substrate utilization in high-fat diet fed mice

OBJECTIVE

The proinflammatory cytokine interleukin-18 (IL-18) putatively modulates food intake and energy metabolism, but the effects of IL-18 in high-fat diet fed animals are unknown. Whether IL-18 alters basal metabolic rate or metabolic processes of living is unknown. Here, we tested the hypothesis that IL-18 modulates weight gain, energy intake, whole-body energy expenditure, and utilization of lipid as a fuel substrate in high-fat diet fed mice.

METHODS

Food intake, whole-body metabolism, and motor activity of IL-18 knockout mice were compared to those of wildtype littermates; anorectic effects of intracerebroventricular IL-18 administration were compared between IL-18 receptor knockout, IL-18/IL-18R knockout and wildtype mice.

RESULTS

Chow-reared IL-18 knockout mice were overweight at 6 months of age and then gained excess weight on both low-fat and high-fat diets, ate more high-fat diet, and showed reduced whole-body energy expenditure and increased respiratory exchange ratios. Reductions in energy expenditure of IL-18 knockout mice were seen across fasting vs. feeding conditions, low- vs. high-fat diets, high vs. low levels of physical activity and times of day, suggesting actions on basal metabolic rate. The circadian amplitude of energy expenditure, but not respiratory exchange ratio, food intake, or motor activity, also was blunted in IL-18 knockout mice. Central IL-18 administration reduced high-fat diet intake in wildtype mice, but not in mice lacking the IL-18 receptor.

CONCLUSION

The loss-of-function results support the hypothesis that endogenous IL-18 suppresses appetite and promote energy expenditure and lipid fuel substrate utilization not only during sickness, but also in healthy adults consuming high-fat diets.

Exercise and diet affect quantitative trait loci for body weight and composition traits in an advanced intercross population of mice

Driven by the recent obesity epidemic, interest in understanding the complex genetic and environmental basis of body weight and composition is great. We investigated this by searching for quantitative trait loci (QTLs) affecting a number of weight and adiposity traits in a G(10) advanced intercross population produced from crosses of mice in inbred strain C57BL/6J with those in a strain selected for high voluntary wheel running. The mice in this population were fed either a high-fat or a control diet throughout the study and also measured for four exercise traits prior to death, allowing us to test for pre- and postexercise QTLs as well as QTL-by-diet and QTL-by-exercise interactions. Our genome scan uncovered a number of QTLs, of which 40% replicated QTLs previously found for similar traits in an earlier (G(4)) generation. For those replicated QTLs, the confidence intervals were reduced from an average of 19 Mb in the G(4) to 8 Mb in the G(10). Four QTLs on chromosomes 3, 8, 13, and 18 were especially prominent in affecting the percentage of fat in the mice. About of all QTLs showed interactions with diet, exercise, or both, their genotypic effects on the traits showing a variety of patterns depending on the diet or level of exercise. It was concluded that the indirect effects of these QTLs provide an underlying genetic basis for the considerable variability in weight or fat loss typically found among individuals on the same diet and/or exercise regimen.

Epistatic Control of Mammary Cancer Susceptibility in Mice may Depend on the Dietary Environment

Recent studies have linked a high fat diet to the development of breast cancer, but any genetic basis for this association is poorly understood. We investigated this association with an epistatic analysis of seven cancer traits in a segregating population of mice with metastatic mammary cancer that were fed either a control or a high-fat diet. We used an interval mapping approach with single nucleotide polymorphisms to scan all 19 autosomes, and discovered a number of diet-independent epistatic interactions of quantitative trait loci (QTLs) affecting these traits. More importantly, we also discovered significant epistatic by diet interactions affecting some of the traits that suggested these epistatic effects varied depending on the dietary environment. An analysis of these interactions showed some were due to epistasis that occurred in mice fed only the control diet or only the high-fat diet whereas other interactions were generated by differential effects of epistasis in the two dietary environments. Some of the epistatic QTLs appeared to colocalize with cancer QTLs mapped in other mouse populations and with candidate genes identified from eQTLs previously mapped in this population, but others represented novel modifying loci affecting these cancer traits. It was concluded that these diet-dependent epistatic QTLs contribute to a genetic susceptibility of dietary effects on breast cancer, and their identification may eventually lead to a better understanding that will be needed for the design of more effective treatments for this disease.

Stitching together multiple data dimensions reveals interacting metabolomic and transcriptomic networks that modulate cell regulation

DNA variation can be used as a systematic source of perturbation in segregating populations as a way to infer regulatory networks via the integration of large-scale, high-dimensional molecular profiling data.

Cells employ multiple levels of regulation, including transcriptional and translational regulation, that drive core biological processes and enable cells to respond to genetic and environmental changes. Small-molecule metabolites are one category of critical cellular intermediates that can influence as well as be a target of cellular regulations. Because metabolites represent the direct output of protein-mediated cellular processes, endogenous metabolite concentrations can closely reflect cellular physiological states, especially when integrated with other molecular-profiling data. Here we develop and apply a network reconstruction approach that simultaneously integrates six different types of data: endogenous metabolite concentration, RNA expression, DNA variation, DNA–protein binding, protein–metabolite interaction, and protein–protein interaction data, to construct probabilistic causal networks that elucidate the complexity of cell regulation in a segregating yeast population. Because many of the metabolites are found to be under strong genetic control, we were able to employ a causal regulator detection algorithm to identify causal regulators of the resulting network that elucidated the mechanisms by which variations in their sequence affect gene expression and metabolite concentrations. We examined all four expression quantitative trait loci (eQTL) hot spots with colocalized metabolite QTLs, two of which recapitulated known biological processes, while the other two elucidated novel putative biological mechanisms for the eQTL hot spots.

It is now possible to score variations in DNA across whole genomes, RNA levels and alternative isoforms, metabolite levels, protein levels and protein state information, protein–protein interactions, and protein–DNA interactions, in a comprehensive fashion in populations of individuals. Interactions among these molecular entities define the complex web of biological processes that give rise to all higher order phenotypes, including disease. The development of analytical approaches that simultaneously integrate different dimensions of data is essential if we are to extract the meaning from large-scale data to elucidate the complexity of living systems. Here, we use a novel Bayesian network reconstruction algorithm that simultaneously integrates DNA variation, RNA levels, metabolite levels, protein–protein interaction data, protein–DNA binding data, and protein–small-molecule interaction data to construct molecular networks in yeast. We demonstrate that these networks can be used to infer causal relationships among genes, enabling the identification of novel genes that modulate cellular regulation. We show that our network predictions either recapitulate known biology or can be prospectively validated, demonstrating a high degree of accuracy in the predicted network.

Sex-, diet-, and cancer-dependent epistatic effects on complex traits in mice

The genetic basis of quantitative traits such as body weight and obesity is complex, with several hundred quantitative trait loci (QTLs) known to affect these and related traits in humans and mice. It also has become increasingly evident that the single-locus effects of these QTLs vary considerably depending on factors such as the sex of the individuals and their dietary environment, and we were interested to know whether this context-dependency also applies to two-locus epistatic effects of QTLs as well. We therefore conducted a genome scan to search for epistatic effects on 13 different weight and adiposity traits in an F₂ population of mice (created from an original intercross of the FVB strain with M16i, a polygenic obesity model) that were fed either a control or a high-fat diet and half of which harbored a transgene (PyMT) that caused the development of metastatic mammary cancer. We used a conventional interval mapping approach with SNPs to scan all 19 autosomes, and found extensive epistasis affecting all of these traits. More importantly, we also discovered that the majority of these epistatic effects exhibited significant interactions with sex, diet, and/or presence of PyMT. Analysis of these interactions showed that many of them appeared to involve QTLs previously identified as affecting these traits, but whose single-locus effects were variously modified by two-locus epistatic effects of other QTLs depending on the sex, diet, or PyMT environment. It was concluded that this context-dependency of epistatic effects is an important component of the genetic architecture of complex traits such as those contributing to weight and obesity.

Dietary fat-dependent transcriptional architecture and copy number alterations associated with modifiers of mammary cancer metastasis

Breast cancer is a complex disease resulting from a combination of genetic and environmental factors. Among environmental factors, body composition and intake of specific dietary components like total fat are associated with increased incidence of breast cancer and metastasis. We previously showed that mice fed a high-fat diet have shorter mammary cancer latency, increased tumor growth and more pulmonary metastases than mice fed a standard diet. Subsequent genetic analysis identified several modifiers of metastatic mammary cancer along with widespread interactions between cancer modifiers and dietary fat. To elucidate diet-dependent genetic modifiers of mammary cancer and metastasis risk, global gene expression profiles and copy number alterations from mammary cancers were measured and expression quantitative trait loci (eQTL) identified. Functional candidate genes that colocalized with previously detected metastasis modifiers were identified. Additional analyses, such as eQTL by dietary fat interaction analysis, causality and database evaluations, helped to further refine the candidate loci to produce an enriched list of genes potentially involved in the pathogenesis of metastatic mammary cancer.

Dietary fat alters pulmonary metastasis of mammary cancers through cancer autonomous and non-autonomous changes in gene expression

Metastasis virulence, a significant contributor to breast cancer prognosis, is influenced by environmental factors like diet. We previously demonstrated in an F2 mouse population generated from a cross between the M16i polygenic obese and MMTV-PyMT mammary cancer models that high fat diet (HFD) decreases mammary cancer latency and increases pulmonary metastases compared to a matched control diet (MCD). Genetic analysis detected eight modifier loci for pulmonary metastasis, and diet significantly interacted with all eight loci. Here, gene expression microarray analysis was performed on mammary cancers from these mice. Despite the substantial dietary impact on metastasis and its interaction with metastasis modifiers, HFD significantly altered the expression of only five genes in mammary tumors; four of which, including serum amyloid A (Saa), are downstream of the tumor suppressor PTEN. Conversely, HFD altered the expression of 211 hepatic genes in a set of tumor free F2 control mice. Independent of diet, pulmonary metastasis virulence correlates with mammary tumor expression of genes involved in endocrine cancers, inflammation, angiogenesis, and invasion. The most significant virulence-associated network harbored genes also found in human adipose or mammary tissue, and contained upregulated Vegfa as a central node. Additionally, expression of Btn1a1, a gene physically located near a putative cis-acting eQTL on chromosome 13 and one of the metastasis modifiers, correlates with metastasis virulence. These data support the existence of diet-dependent and independent cancer modifier networks underlying differential susceptibility to mammary cancer metastasis and suggest that diet influences cancer metastasis virulence through tumor autonomous and non-autonomous mechanisms.

Genetic resistance to diet-induced obesity in chromosome substitution strains of mice

Discovery of genes that confer resistance to diseases such as diet-induced obesity could have tremendous therapeutic impact. We previously demonstrated that the C57BL/6J-Chr(A/J)/NaJ panel of chromosome substitution strains (CSSs) is a unique model for studying resistance to diet-induced obesity. In the present study, three replicate CSS surveys showed remarkable consistency, with 13 A/J-derived chromosomes reproducibly conferring resistance to high-fat-diet-induced obesity. Twenty CSS intercrosses, one derived from each of the 19 autosomes and chromosome X, were used to determine the number and location of quantitative trait loci (QTLs) on individual chromosomes and localized six QTLs. However, analyses of mean body weight in intercross progeny versus C57BL/6J provided strong evidence that many QTLs discovered in the CSS surveys eluded detection in these CSS intercrosses. Studies of the temporal effects of these QTLs suggest that obesity resistance was dynamic, with QTLs acting at different ages or after different durations of diet exposure. Thus, these studies provide insight into the genetic architecture of complex traits such as resistance to diet-induced obesity in the C57BL/6J-Chr(A/J)/NaJ CSSs. Because some of the QTLs detected in the CSS intercrosses were not detected using a traditional C57BL/6J x A/J intercross, our results demonstrate that surveys of CSSs and congenic strains derived from them are useful complementary tools for analyzing complex traits.

Genotype X diet interactions in mice predisposed to mammary cancer: II. Tumors and metastasis

High dietary fat intake and obesity may increase the risk of susceptibility to certain forms of cancer. To study the interactions of dietary fat, obesity, and metastatic mammary cancer, we created a population of F(2) mice cosegregating obesity QTL and the MMTV-PyMT transgene. We fed the F(2) mice either a very high-fat or a matched-control-fat diet, and we measured growth, body composition, age at mammary tumor onset, tumor number and severity, and formation of pulmonary metastases. SNP genotyping across the genome facilitated analyses of QTL and QTL x diet interaction effects. Here we describe effects of diet on mammary tumor and metastases phenotypes, mapping of tumor/metastasis modifier genes, and the interaction between dietary fat levels and effects of cancer modifiers. Results demonstrate that animals fed a high-fat diet are not only more likely to experience decreased mammary cancer latency but increased tumor growth and pulmonary metastases occurrence over an equivalent time. We identified 25 modifier loci for mammary cancer and pulmonary metastasis, likely representing 13 unique loci after accounting for pleiotropy, and novel QTL x diet interactions at a majority of these loci. These findings highlight the importance of accurately modeling not only the human cancer characteristics in mice but also the environmental exposures of human populations.