Genetic Background Shapes Phenotypic Response to Diet for Adiposity in the Collaborative Cross

Systems genetics of metabolic health in the BXD mouse genetic reference population

Susceptibility to metabolic syndrome (MetS) is dependent on genetics, environment, and gene-by-environment interactions, rendering the study of underlying mechanisms challenging. The majority of experiments in model organisms do not incorporate genetic variation and lack specific evaluation criteria for MetS. Here, we derived a continuous metric, the metabolic health score (MHS), based on standard clinical parameters and defined its molecular signatures in the liver and circulation. In human UK Biobank, the MHS associated with MetS status and was predictive of future disease incidence, even in individuals without MetS. Using quantitative trait locus analyses in mice, we found two MHS-associated genetic loci and replicated them in unrelated mouse populations. Through a prioritization scheme in mice and human genetic data, we identified TNKS and MCPH1 as candidates mediating differences in the MHS. Our findings provide insights into the molecular mechanisms sustaining metabolic health across species and uncover likely regulators. A record of this paper's transparent peer review process is included in the supplemental information.

ANMCO (Italian Association of Hospital Cardiologists) scientific statement: obesity in adults-an approach for cardiologists

Obesity is a complex, chronic disease requiring a multidisciplinary approach to its management. In clinical practice, body mass index and waist-related measurements can be used for obesity screening. The estimated prevalence of obesity among adults worldwide is 12%. With the expected further increase in overall obesity prevalence, clinicians will increasingly be managing patients with obesity. Energy balance is regulated by a complex neurohumoral system that involves the central nervous system and circulating mediators, among which leptin is the most studied. The functioning of these systems is influenced by both genetic and environmental factors. Obesity generally occurs when a genetically predisposed individual lives in an obesogenic environment for a long period. Cardiologists are deeply involved in evaluating patients with obesity. Cardiovascular risk profile is one of the most important items to be quantified to understand the health risk due to obesity and the clinical benefit that a single patient can obtain with weight loss. At the individual level, appropriate patient involvement, the detection of potential obesity causes, and a multidisciplinary approach are tools that can improve clinical outcomes. In the near future, we will probably have new pharmacological tools at our disposal that will facilitate achieving and maintaining weight loss. However, pharmacological treatment alone cannot cure such a complex disease. The aim of this paper is to summarize some key points of this field, such as obesity definition and measurement tools, its epidemiology, the main mechanisms underlying energy homeostasis, health consequences of obesity with a focus on cardiovascular diseases and the obesity paradox.Level of evidence V: report of expert committees.

Genetic diet interactions of ACE: the increased hypertension predisposition in the Latin American population

Hypertension is one of the primary risk factors associated with cardiovascular diseases (CVDs). It is a condition that affects people worldwide, and its prevalence is increasing due to several factors, such as lack of physical activity, population aging, and unhealthy diets. Notably, this increase has primarily occurred in low and middle-income countries (LMICs). In Latin America, approximately 40% of adults have been diagnosed with hypertension. Moreover, reports have shown that the Latin American genetic composition is highly diverse, and this genetic background can influence various biological processes, including disease predisposition and treatment effectiveness. Research has shown that Western dietary patterns, which include increased consumption of red meat, refined grains, sugar, and ultra-processed food, have spread across the globe, including Latin America, due to globalization processes. Furthermore, a higher than recommended sodium consumption, which has been associated with hypertension, has been identified across different regions, including Asia, Europe, America, Oceania, and Africa. In conclusion, hypertension is a multifactorial disease involving environmental and genetic factors. In Latin America, hypertension prevalence is increasing due to various factors, including age, the adoption of a "Westernized" diet, and potential genetic predisposition factors involving the ACE gene. Furthermore, identifying the genetic and molecular mechanisms of the disease, its association with diet, and how they interact is essential for the development of personalized treatments to increase its efficacy and reduce side effects.

Translating energy balance research from the bench to the clinic to the community: Parallel animal-human studies in cancer

Advances in energy balance and cancer research to date have largely occurred in siloed work in rodents or patients. However, substantial benefit can be derived from parallel studies in which animal models inform the design of clinical and population studies or in which clinical observations become the basis for animal studies. The conference Translating Energy Balance from Bench to Communities: Application of Parallel Animal-Human Studies in Cancer, held in July 2021, convened investigators from basic, translational/clinical, and population science research to share knowledge, examples of successful parallel studies, and strong research to move the field of energy balance and cancer toward practice changes. This review summarizes key topics discussed to advance research on the role of energy balance, including physical activity, body composition, and dietary intake, on cancer development, cancer outcomes, and healthy survivorship.

Unraveling the Host Genetic Background Effect on Internal Organ Weight Influenced by Obesity and Diabetes Using Collaborative Cross Mice

Type 2 diabetes mellitus (T2DM) is a severe chronic epidemic that results from the body's improper usage of the hormone insulin. Globally, 700 million people are expected to have received a diabetes diagnosis by 2045, according to the International Diabetes Federation (IDF). Cancer and macro- and microvascular illnesses are only a few immediate and long-term issues it could lead to. T2DM accelerates the effect of organ weights by triggering a hyperinflammatory response in the body's organs, inhibiting tissue repair and resolving inflammation. Understanding how genetic variation translates into different clinical presentations may highlight the mechanisms through which dietary elements may initiate or accelerate inflammatory disease processes and suggest potential disease-prevention techniques. To address the host genetic background effect on the organ weight by utilizing the newly developed mouse model, the Collaborative Cross mice (CC). The study was conducted on 207 genetically different CC mice from 8 CC lines of both sexes. The experiment started with 8-week-old mice for 12 weeks. During this period, one group maintained a standard chow diet (CHD), while the other group maintained a high-fat diet (HFD). In addition, body weight was recorded bi-weekly, and at the end of the study, a glucose tolerance test, as well as tissue collection (liver, spleen, heart), were conducted. Our study observed a strong effect of HFD on blood glucose clearance among different CC lines. The HFD decreased the blood glucose clearance displayed by the significant Area Under Curve (AUC) values in both populations. In addition, variation in body weight changes among the different CC lines in response to HFD. The female liver weight significantly increased compared to males in the overall population when exposed to HFD. Moreover, males showed higher heritability values than females on the same diet. Regardless of the dietary challenge, the liver weight in the overall male population correlated positively with the final body weight. The liver weight results revealed that three different CC lines perform well under classification models. The regression results also varied among organs. Accordingly, the differences among these lines correspond to the genetic variance, and we suspect that some genetic factors invoke different body responses to HFD. Further investigations, such as quantitative trait loci (QTL) analysis and genomic studies, could find these genetic elements. These findings would prove critical factors for developing personalized medicine, as they could indicate future body responses to numerous situations early, thus preventing the development of complex diseases.

Which mouse multiparental population is right for your study? The Collaborative Cross inbred strains, their F1 hybrids, or the Diversity Outbred population

Multiparental populations (MPPs) encompass greater genetic diversity than traditional experimental crosses of two inbred strains, enabling broader surveys of genetic variation underlying complex traits. Two such mouse MPPs are the Collaborative Cross (CC) inbred panel and the Diversity Outbred (DO) population, which are descended from the same eight inbred strains. Additionally, the F1 intercrosses of CC strains (CC-RIX) have been used and enable study designs with replicate outbred mice. Genetic analyses commonly used by researchers to investigate complex traits in these populations include characterizing how heritable a trait is, i.e. its heritability, and mapping its underlying genetic loci, i.e. its quantitative trait loci (QTLs). Here we evaluate the relative merits of these populations for these tasks through simulation, as well as provide recommendations for performing the quantitative genetic analyses. We find that sample populations that include replicate animals, as possible with the CC and CC-RIX, provide more efficient and precise estimates of heritability. We report QTL mapping power curves for the CC, CC-RIX, and DO across a range of QTL effect sizes and polygenic backgrounds for samples of 174 and 500 mice. The utility of replicate animals in the CC and CC-RIX for mapping QTLs rapidly decreased as traits became more polygenic. Only large sample populations of 500 DO mice were well-powered to detect smaller effect loci (7.5-10%) for highly complex traits (80% polygenic background). All results were generated with our R package musppr, which we developed to simulate data from these MPPs and evaluate genetic analyses from user-provided genotypes.

Overexpressing high levels of human vaspin limits high fat diet-induced obesity and enhances energy expenditure in a transgenic mouse

Adipose tissue inflammation and insulin resistance are hallmarks in the development of metabolic diseases resulting from overweight and obesity, such as type 2 diabetes and non-alcoholic fatty liver disease. In obesity, adipocytes predominantly secrete proinflammatory adipokines that further promote adipose tissue dysfunction with negative effects on local and systemic insulin sensitivity. Expression of the serpin vaspin (SERPINA12) is also increased in obesity and type 2 diabetes, but exhibits compensatory roles in inflammation and insulin resistance. This has in part been demonstrated using vaspin-transgenic mice. We here report a new mouse line (h-vaspinTG) with transgenic expression of human vaspin in adipose tissue that reaches vaspin concentrations three orders of magnitude higher than wild type controls (>200 ng/ml). Phenotyping under chow and high-fat diet conditions included glucose-tolerance tests, measurements of energy expenditure and circulating parameters, adipose tissue and liver histology. Also, ex vivo glucose uptake in isolated adipocytes and skeletal muscle was analyzed in h-vaspinTG and littermate controls. The results confirmed previous findings, revealing a strong reduction in diet-induced weight gain, fat mass, hyperinsulinemia, -glycemia and -cholesterolemia as well as fatty liver. Insulin sensitivity in adipose tissue and muscle was not altered. The h-vaspinTG mice showed increased energy expenditure under high fat diet conditions, that may explain reduced weight gain and overall metabolic improvements. In conclusion, this novel human vaspin-transgenic mouse line will be a valuable research tool to delineate whole-body, tissue- and cell-specific effects of vaspin in health and disease.

Altered macronutrient composition and genetics influence the complex transcriptional network associated with adiposity in the Collaborative Cross

Background

Obesity is a serious disease with a complex etiology characterized by overaccumulation of adiposity resulting in detrimental health outcomes. Given the liver’s critical role in the biological processes that attenuate adiposity accumulation, elucidating the influence of genetics and dietary patterns on hepatic gene expression is fundamental for improving methods of obesity prevention and treatment. To determine how genetics and diet impact obesity development, mice from 22 strains of the genetically diverse recombinant inbred Collaborative Cross (CC) mouse panel were challenged to either a high-protein or high-fat high-sucrose diet, followed by extensive phenotyping and analysis of hepatic gene expression.

Results

Over 1000 genes differentially expressed by perturbed dietary macronutrient composition were enriched for biological processes related to metabolic pathways. Additionally, over 9000 genes were differentially expressed by strain and enriched for biological process involved in cell adhesion and signaling. Weighted gene co-expression network analysis identified multiple gene clusters (modules) associated with body fat % whose average expression levels were influenced by both dietary macronutrient composition and genetics. Each module was enriched for distinct types of biological functions.

Conclusions

Genetic background affected hepatic gene expression in the CC overall, but diet macronutrient differences also altered expression of a specific subset of genes. Changes in macronutrient composition altered gene expression related to metabolic processes, while genetic background heavily influenced a broad range of cellular functions and processes irrespective of adiposity. Understanding the individual role of macronutrient composition, genetics, and their interaction is critical to developing therapeutic strategies and policy recommendations for precision nutrition.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12263-022-00714-x.

Utilizing preclinical models of genetic diversity to improve translation of phytochemical activities from rodents to humans and inform personalized nutrition

Mouse models are an essential tool in different areas of research, including nutrition and phytochemical research. Traditional inbred mouse models have allowed the discovery of therapeutical targets and mechanisms of action and expanded our knowledge of health and disease. However, these models lack the genetic variability typically found in human populations, which hinders the translatability of the results found in mice to humans. The development of genetically diverse mouse models, such as the collaborative cross (CC) or the diversity outbred (DO) models, has been a useful tool to overcome this obstacle in many fields, such as cancer, immunology and toxicology. However, these tools have not yet been widely adopted in the field of phytochemical research. As demonstrated in other disciplines, use of CC and DO models has the potential to provide invaluable insights for translation of phytochemicals from rodents to humans, which are desperately needed given the challenges and numerous failed clinical trials in this field. These models may prove informative for personalized use of phytochemicals in humans, including: predicting interindividual variability in phytochemical bioavailability and efficacy, identifying genetic loci or genes governing response to phytochemicals, identifying phytochemical mechanisms of action and therapeutic targets, and understanding the impact of genetic variability on individual response to phytochemicals. Such insights would prove invaluable for personalized implementation of phytochemicals in humans. This review will focus on the current work performed with genetically diverse mouse populations, and the research opportunities and advantages that these models can offer to phytochemical research.