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

宏量营养素和代谢健康 - 使用代谢组学和脂质组学了解代谢疾病如何在人群水平上出现。

• 批准号: MR/P011705/2
• 负责人: Julian Griffin
• 金额: $ 62.06万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FP011705%2F2
• 关键词: Macronutrients; Metabolic; Health; Understanding; how

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.

肥胖和2型糖尿病（T2DM）在英国都在增加，给国民健康服务带来了巨大的压力，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脂肪和糖的饮食消费增加以及身体活动的普遍减少有关。虽然目前的公共健康建议是多运动，少吃热量密集的食物，但这种健康建议无法阻止肥胖或T2DM的增加。虽然有许多药物用于治疗T2DM和肥胖个体血液中发现的脂肪浓度增加，但许多药物具有使其长期使用复杂化的副作用，并且管理成本高。糖尿病研究领域的一个中心问题是，为什么在个体的基础上，某些人倾向于发展胰岛素抵抗（糖尿病前期状态）和随后的T2DM，而其他人则保持代谢健康。解决这个问题可以帮助治疗那些有进展风险的人，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，包括质谱和核磁共振（NMR）光谱，来测量组织的总小分子补体，细胞和生物流体，以使用多变量统计和模式识别技术的组合开发与疾病相关的那些代谢物的指纹。这种方法被称为代谢组学。通过模拟这些代谢物随着疾病进展的变化，我们建立了一个与疾病相关的关键代谢扰动的反应“图谱”。特别是这种方法可以让我们看看食物摄入量如何影响身体的新陈代谢，我们可以模拟这些变化，看看营养过剩（吃太多的食物）引起的饮食基因型相互作用。为了实现这一目标，我们已经确定了四个主题并行开发。1.健康和疾病中的脂肪细胞：众所周知，脂肪细胞（称为白色脂肪组织）除了作为脂肪储存的主要场所外，还在维持健康代谢方面发挥着许多重要作用，包括调节激素，维持体温甚至有助于生物钟。我们将应用代谢组学结合分子生物学工具来研究脂质储存之间的平衡以及我们如何影响脂肪代谢以减少肥胖。2.异位脂肪沉积：一旦超过了白色脂肪组织储存脂肪的能力，脂肪就会不适当地（异位地）沉积在其他组织中。虽然血糖升高的后果在生物化学上是明确的，但我们不知道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分析肝脏，心脏和骨骼肌中过量脂肪储存的影响，特别是关注脂肪肝疾病的进展。3.流行病学规模的脂质组学：虽然大多数动物模型是由导致T2DM的单个基因的罕见错误引起的，但糖尿病患者中发现的最常见形式是由许多具有强烈环境相互作用的基因引起的，特别是由于营养过剩和久坐不动的生活方式增加。为了研究IR和T2DM在人类中的发展，我们开发了可以在全球范围内进行的测定，以使我们能够解决流行病学研究中有关T2DM和饮食、种族和年龄的问题。质谱和生物信息学方法开发：为了能够进行这些研究，我们需要在质谱和处理数据的数学工具方面处于发展的最前沿。我们目前正在开发用于脂质组学的质谱成像和离子迁移率工具。

项目成果

Gene and metabolite expression dependence on body mass index in human myocardium.

• DOI: 10.1038/s41598-022-05562-8
• 发表时间: 2022-01-26
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Adebayo AS;Roman M;Zakkar M;Yusoff S;Gulston M;Joel-David L;Anthony B;Lai FY;Murgia A;Eagle-Hemming B;Sheikh S;Kumar T;Aujla H;Dott W;Griffin JL;Murphy GJ;Woźniak MJ
• 通讯作者: Woźniak MJ

Mapping Rora expression in resting and activated CD4+ T cells.

• DOI: 10.1371/journal.pone.0251233
• 发表时间: 2021
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Haim-Vilmovsky L;Henriksson J;Walker JA;Miao Z;Natan E;Kar G;Clare S;Barlow JL;Charidemou E;Mamanova L;Chen X;Proserpio V;Pramanik J;Woodhouse S;Protasio AV;Efremova M;Griffin JL;Berriman M;Dougan G;Fisher J;Marioni JC;McKenzie ANJ;Teichmann SA
• 通讯作者: Teichmann SA

SARS-CoV-2 Omicron-B.1.1.529 leads to widespread escape from neutralizing antibody responses.

• DOI: 10.1016/j.cell.2021.12.046
• 发表时间: 2022-02-03
• 期刊: Cell
• 影响因子: 64.5
• 作者: Dejnirattisai W;Huo J;Zhou D;Zahradník J;Supasa P;Liu C;Duyvesteyn HME;Ginn HM;Mentzer AJ;Tuekprakhon A;Nutalai R;Wang B;Dijokaite A;Khan S;Avinoam O;Bahar M;Skelly D;Adele S;Johnson SA;Amini A;Ritter TG;Mason C;Dold C;Pan D;Assadi S;Bellass A;Omo-Dare N;Koeckerling D;Flaxman A;Jenkin D;Aley PK;Voysey M;Costa Clemens SA;Naveca FG;Nascimento V;Nascimento F;Fernandes da Costa C;Resende PC;Pauvolid-Correa A;Siqueira MM;Baillie V;Serafin N;Kwatra G;Da Silva K;Madhi SA;Nunes MC;Malik T;Openshaw PJM;Baillie JK;Semple MG;Townsend AR;Huang KA;Tan TK;Carroll MW;Klenerman P;Barnes E;Dunachie SJ;Constantinides B;Webster H;Crook D;Pollard AJ;Lambe T;OPTIC Consortium;ISARIC4C Consortium;Paterson NG;Williams MA;Hall DR;Fry EE;Mongkolsapaya J;Ren J;Schreiber G;Stuart DI;Screaton GR
• 通讯作者: Screaton GR

Histone acetyltransferase NAA40 modulates acetyl-CoA levels and lipid synthesis.

组蛋白乙酰转移酶NAA40调节乙酰-COA水平和脂质合成。

• DOI: 10.1186/s12915-021-01225-8
• 发表时间: 2022-01-20
• 期刊: BMC biology
• 影响因子: 5.4
• 作者: Charidemou E;Tsiarli MA;Theophanous A;Yilmaz V;Pitsouli C;Strati K;Griffin JL;Kirmizis A
• 通讯作者: Kirmizis A

Decreased Fatty Acid Transporter FABP1 and Increased Isoprostanes and Neuroprostanes in the Human Term Placenta: Implications for Inflammation and Birth Weight in Maternal Pre-Gestational Obesity.

• DOI: 10.3390/nu13082768
• 发表时间: 2021-08-12
• 期刊: Nutrients
• 影响因子: 5.9
• 作者: Belcastro L;Ferreira CS;Saraiva MA;Mucci DB;Murgia A;Lai C;Vigor C;Oger C;Galano JM;Pinto GDA;Griffin JL;Torres AG;Durand T;Burton GJ;Sardinha FLC;El-Bacha T
• 通讯作者: El-Bacha T