Macronutrients and Metabolic Health - Understanding how metabolic disease arises at the population level using metabolomics and lipidomics.

在英国，肥胖症和2型糖尿病(T2 DM)都在增加，这给英国国家医疗服务体系带来了巨大的压力，并影响了英国的健康。我们知道，这些增加的一些主要原因与饮食中脂肪和糖的摄入量增加以及体力活动普遍减少有关。虽然目前的公共健康建议是多锻炼，少吃高热量食物，但这个健康建议一直无法阻止肥胖症或2型糖尿病的增加。虽然有许多药物用于治疗T2 DM和肥胖症患者血液中脂肪浓度的增加，但许多药物都有副作用，使其长期使用变得复杂，而且管理成本高昂。糖尿病研究领域的一个核心问题是，为什么某些人在个体基础上容易患上胰岛素抵抗(糖尿病前期状态)和随后的T2 DM，而另一些人则保持新陈代谢健康。解决这个问题可以帮助治疗那些有发展风险的人，并对治疗这种疾病及其并发症的成本产生重大影响。为了做到这一点，我们使用分析化学技术，包括质谱学和核磁共振(核磁共振)光谱，来测量组织、细胞和生物液的总小分子组成，利用多变量统计和模式识别技术的组合来开发与疾病相关的代谢物的指纹。这种方法被称为代谢组学。通过模拟这些代谢物在疾病进展过程中的变化，我们建立了一个与疾病相关的关键代谢扰动方面的反应“图谱”。特别是，这种方法使我们能够看到食物摄入如何影响身体的新陈代谢，我们可以对这些变化进行建模，以查看由过度营养(吃太多食物)引起的饮食-基因相互作用。为了实现这一目标，我们确定了四个平行发展的主题1。脂肪细胞与健康和疾病：众所周知，脂肪细胞(称为白色脂肪组织)除了作为脂肪的主要储存场所外，还在维持健康的新陈代谢方面发挥着许多重要作用，包括调节激素、维持体温，甚至对生物钟做出贡献。我们将结合代谢组学和分子生物学工具来研究脂肪储存和我们如何影响脂肪代谢以减少肥胖之间的平衡。2.异位脂肪沉积：一旦白色脂肪组织储存脂肪的能力被超过，其他组织中就会出现不适当的(异位)脂肪沉积。虽然血糖升高的后果在生化上有很好的定义，但我们并不了解脂肪浓度升高的后果是什么。我们将使用全面的代谢组学方法来描述肝脏、心脏和骨骼肌中过度脂肪储存的影响，特别是关注脂肪肝疾病的进展。3.流行病学中的脂质组学：虽然大多数动物模型是由导致T2 DM的单个基因的罕见错误引起的，但糖尿病患者中最常见的形式是由许多基因与强烈的环境相互作用引起的，特别是营养过剩和久坐不动的生活方式的结果。为了研究胰岛素抵抗和2型糖尿病在人类中的发展，我们开发了可以在全球范围内进行的分析，使我们能够在流行病学研究中解决有关T2 DM和饮食、种族和年龄的问题。质谱学和生物信息学的方法发展：为了能够进行这些研究，我们需要处于质谱学和处理数据的数学工具的发展的前沿。我们目前正在为脂质组学开发质谱学成像和离子迁移率方面的工具。

Both obesity and type 2 diabetes (T2DM) are increasing in the UK, placing significant pressure on the National Health Service and impacting on the health of the UK. We know that some of the major causes of these increases are associated with increased dietary consumption of fats and sugars, as well as a general decrease in physical activity. While current public health advice is to exercise more and eat less calorie dense foods, this health advice has been unable to halt the increases in either obesity or T2DM. While there are a number of drugs used to treat T2DM and the increased fat concentrations found in the blood of individuals with obesity, many have side effects which complicate their long term use and are costly to administer. One central question to the field of diabetes research is why on an individual basis certain people are predisposed to developing insulin resistance (a pre-diabetic state) and subsequent T2DM while others stay metabolically healthy. Addressing this question could help treat those at risk of progression and have a significant impact on the costs of treating this disease and its complications.In order to do this we use analytical chemistry techniques, including mass spectrometry and Nuclear Magnetic Resonance (NMR) spectroscopy, to measure the total small molecule complement of tissues, cells and biofluids to develop a fingerprint of those metabolites that are associated with disease using a combination of multivariate statistics and pattern recognition techniques. This approach is termed metabolomics. By modelling changes in these metabolites as disease progresses we build up an 'atlas' of response in terms of the key metabolic perturbations associated with the disease. In particular this approach allows us to look at how food intake influences the metabolism of the body, and we can model these changes to look at diet-genotype interactions induced by over-nutrition (eating too much food).To achieve this aim we have identified four themes to be developed in parallel.1. Fat cells in health and disease: It is well established that fat cells (referred to as white adipose tissue) have numerous important roles in maintaining healthy metabolism in addition to their role as a major site for storage of fats, including roles in regulating hormones, maintaining body temperature and even contributing to the body clock. We will apply metabolomics in conjunction with molecular biology tools to investigate the balance between lipid storage and how we might influence fat metabolism to reduce obesity. 2. Ectopic fat deposition: Once the capability of white adipose tissue to store fat has been exceeded, fat deposition occurs inappropriately (ectopically) in other tissues. While the consequences of raised blood glucose are biochemically well defined, we do not understand what the consequences of raised fat concentrations are. We will use comprehensive metabolomic approaches to profile the impact of excessive fat storage in the liver, heart and skeletal muscle, and in particular focus on the progression of fatty liver disease. 3. Lipidomics at the epidemiology scale: While most animal models are caused by rare errors in single genes which cause T2DM, the most common forms found in patients with diabetes are caused by many genes with a strong environmental interaction, particularly as the result of over nutrition and increased sedentary lifestyles. In order to investigate IR and T2DM development in humans we have developed assays that can be performed on a global scale to allow us to address questions about T2DM and diet, ethnicity and age in epidemiology studies.4. Method development in mass spectrometry and bioinformatics: To be able to conduct these studies we require being at the forefront of developments in both mass spectrometry and mathematical tools for processing the data. We are currently developing tools in mass spectrometry imagining and ion mobility for lipidomics.