A study of Integrated multi-organ, multi-omic, and gut microbiome signatures of fat and sucrose dietary oversupply in cardiometabolic disease. Liu et al.

Cardiometabolic disease is the greatest challenge facing global health. Increasingly, evidence suggests that Western diet comprising an over-supply of energy from fat and sucrose leads to obesity, insulin resistance, hypertension, and cardiovascular disease. Traditional preclinical animal studies of cardiometabolic disease often adopt a reductionist approach, focusing on individual components. To overcome this, we comprehensively assessed cardiometabolic phenotypes - anthropometric, physiological, and metabolic – along with the molecular changes consequent upon fat or sucrose dietary over-supply, or both in male C57BL/6J mice. Molecular assessment included measurement of the gut microbiome and several metabolite pools including plasma, heart, liver, and gut contents (cecal and fecal). In these mice, we identified key changes across phenotypes, metabolites, microbiota, and their inter-relationship, and synthesized all the data into 4 distinct phenogroups that explain the variance across cardiometabolic parameters. The molecular components of each phenogroup reveal new insight into inter-organ regulation of Western diet-dependent cardiometabolic phenotypes and highlight important avenues for further study.

Mice were allocated to four different diets consisting of a control diet (CHOW), a high-sucrose diet (HSD), a high-fat diet (HFD), and a high-fat high-sucrose (western) diet (HFSD). Physiological, metabolic and echocardiographic measurements were performed on these mice during a 30-week diet protocol and metabolomics and microbiome data was collected after euthanization.

Data were analyzed in a two-by-two factorial framework, testing for main effects of high-fat, and high-sugar as well as a high-fat-high-sugar interaction, treating the chow-fed group as the control. Where we have repeated measures over time (e.g., body mass, food intake etc), outcomes were analyzed using a generalized additive mixed model (GAMM), treating animal ID and cage as random effects, time as a non-parametric smooth term, and dietary fat and sugar as parametric fixed effects with an interaction. For outcomes measured at a single time-point (i.e., without repeated measures), data were analyzed using linear-mixed effects models (LMMs) with cage as a random effect and dietary fat and sugar as fixed effects with an interaction. Data were analyzed and plots made in the statistical programming environment R, with GAMMs implemented using the ‘gam’ function in mgcv, and LMMs implemented using the ‘lmer’ function in lme4 58-60. To ascertain the statistical significance of main and interactive effects of the dietary exposures ANOVA-tables were created for models using the ‘anova’ function (lmerTest and mgcv packages). Data were visualized using ggplot2. Principle component analysis (PCA) was implemented using the ‘princomp’ function in R.

心血管代谢性疾病是全球公共卫生所面临的重大挑战。越来越多的证据表明，以脂肪和蔗糖能量供应过剩为特征的西方饮食，导致肥胖、胰岛素抵抗、高血压和心血管疾病。传统的关于心血管代谢性疾病的前临床动物研究通常采用还原论方法，聚焦于单一成分。为了克服这一局限，我们对心血管代谢表型——包括人体测量学、生理学和代谢学——以及由脂肪或蔗糖饮食过度供应或两者兼而有之引起的分子变化进行了全面评估，这些变化发生在雄性C57BL/6J小鼠身上。分子评估包括肠道微生物组和包括血浆、心脏、肝脏和肠道内容物（盲肠和粪便）在内的多个代谢物库的测量。在这些小鼠中，我们确定了跨表型、代谢物、微生物群及其相互关系的关键变化，并将所有数据综合为4个不同的表型组，这些表型组解释了心血管代谢参数之间的差异。每个表型组的分子成分揭示了关于西方饮食依赖的心血管代谢表型器官间调节的新见解，并突出了进一步研究的重点领域。

小鼠被分配到四种不同的饮食中，包括对照组饮食（CHOW）、高蔗糖饮食（HSD）、高脂肪饮食（HFD）以及高脂肪高蔗糖（西方）饮食（HFSD）。在为期30周的营养方案期间，对小鼠进行了生理学、代谢学和超声心动图测量，并在安乐死之后收集了代谢组和微生物组数据。

数据在二因素框架下进行分析，测试高脂肪、高糖以及高脂肪-高糖相互作用的主效应，将CHOW饲养组视为对照组。对于时间序列上的重复测量（例如，体重、食物摄入等），结果使用广义加性混合模型（GAMM）进行分析，将动物ID和笼子作为随机效应，时间作为非参数平滑项，饮食脂肪和糖作为参数固定效应，并考虑其相互作用。对于在单一时间点测量的结果（即无重复测量），数据使用线性混合效应模型（LMMs）进行分析，将笼子作为随机效应，饮食脂肪和糖作为固定效应，并考虑其相互作用。数据分析和绘图在统计编程环境R中进行，GAMMs使用mgcv包中的'gam'函数实现，LMMs使用lme4包中的'lmer'函数实现。为了确定饮食暴露的主要和交互效应的统计学意义，使用'anova'函数（lmerTest和mgcv包）创建了ANOVA表。数据可视化使用ggplot2进行。主成分分析（PCA）使用R中的'princomp'函数实现。