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


Ontology type: schema:MonetaryGrant     


Grant Info

YEARS

2016-2019

FUNDING AMOUNT

2089805.0 GBP

ABSTRACT

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. Technical Summary Both obesity and type 2 diabetes (T2DM) are increasing in the UK impacting on the nation's health. We aim to address this major health issue by understanding the interactions between over nutrition, subsequent obesity, and the development of insulin resistance (IR), and how this ultimately leads to T2DM and cardiovascular disease. Our global aim is to understand the underlying mechanisms that determine why on an individual basis certain people are predisposed to developing IR and subsequently T2DM, while others stay metabolically healthy. To achieve this aim we have identified four themes to be developed in parallel. 1. White adipose tissue (WAT) function in health and disease: We will apply metabolomics in conjunction with molecular biology tools to investigate the balance between lipid storage and oxidation, and in particular continue our study of the browning of WAT. Furthermore, using measurements of lipid mediators we will investigate further how over nutrition produces adipose tissue dysfunction and inflammation. 2. Ectopic fat deposition: We will use comprehensive metabolomic and lipidomic mass spectrometry approaches to profile the impact of excessive fat storage in the liver, heart and skeletal muscle, and in particular focus on the transition of non-alcoholic fatty liver disease to non-alcoholic steatohepatitis and cirrhosis, the development of ER-stress in skeletal muscle, and how diet influences cell membrane composition and ultimately cellular function across the body. 3. Lipidomics at the epidemiology scale: 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. These will be applied to large scale studies (n>5000) such as Fenland, PROMIS and INTERVAL. 4. Method development in mass spectrometry and bioinformatics: We are currently developing tools in mass spectrometry imaging and ion mobility for lipidomics. More... »

URL

https://gtr.ukri.org/project/A3F926D6-C2EB-49B8-BC20-218BFD6440AA

Related SciGraph Publications

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  • 2018-03-19. Author Correction: Cross sectional evaluation of the gut-microbiome metabolome axis in an Italian cohort of IBD patients in SCIENTIFIC REPORTS
  • 2018-03-17. Interplay between genetic predisposition, macronutrient intake and type 2 diabetes incidence: analysis within EPIC-InterAct across eight European countries in DIABETOLOGIA
  • 2018-03-16. KniMet: a pipeline for the processing of chromatography–mass spectrometry metabolomics data in METABOLOMICS
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  • 2016-01-29. From genomic medicine to precision medicine: highlights of 2015 in GENOME MEDICINE
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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.\n\nIn 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).\n\nTo achieve this aim we have identified four themes to be developed in parallel.\n\n1. 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. \n\n2. 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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. 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Ectopic fat deposition: We will use comprehensive metabolomic and lipidomic mass spectrometry approaches to profile the impact of excessive fat storage in the liver, heart and skeletal muscle, and in particular focus on the transition of non-alcoholic fatty liver disease to non-alcoholic steatohepatitis and cirrhosis, the development of ER-stress in skeletal muscle, and how diet influences cell membrane composition and ultimately cellular function across the body. 3. Lipidomics at the epidemiology scale: 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. These will be applied to large scale studies (n>5000) such as Fenland, PROMIS and INTERVAL. 4. Method development in mass spectrometry and bioinformatics: We are currently developing tools in mass spectrometry imaging and ion mobility for lipidomics.
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    87 fat
    88 fat cells
    89 fat concentration
    90 fat deposition
    91 fat metabolism
    92 fat storage
    93 fatty liver disease
    94 field
    95 fingerprints
    96 focus
    97 food
    98 forefront
    99 forefront of developments
    100 form
    101 function
    102 general decrease
    103 genes
    104 global aim
    105 global scale
    106 glucose
    107 health
    108 health advice
    109 health issues
    110 health services
    111 health understanding
    112 healthy metabolism
    113 heart
    114 hormone
    115 humans
    116 imaging
    117 imaginings
    118 impact
    119 important role
    120 increase
    121 individuals
    122 inflammation
    123 influence
    124 insulin resistance
    125 interaction
    126 intervals
    127 ion mobility
    128 issues
    129 large-scale studies
    130 levels
    131 lifestyle
    132 lipid mediators
    133 lipid storage
    134 lipidomics
    135 liver
    136 liver disease
    137 long-term use
    138 macronutrients
    139 magnetic resonance spectroscopy
    140 major cause
    141 major health issue
    142 major site
    143 mass spectrometry
    144 mass spectrometry imaging
    145 mathematical tools
    146 measurements
    147 mechanism
    148 mediators
    149 membrane composition
    150 metabolic diseases
    151 metabolic perturbations
    152 metabolism
    153 metabolites
    154 metabolomics
    155 metabolomics approach
    156 method development
    157 mobility
    158 model
    159 molecular biology tools
    160 most animal models
    161 multivariate statistics
    162 muscle
    163 nation's health
    164 non-alcoholic fatty liver disease
    165 non-alcoholic steatohepatitis
    166 nuclear magnetic resonance spectroscopy
    167 number
    168 number of drugs
    169 numerous important roles
    170 nutrition
    171 obesity
    172 order
    173 oxidation
    174 parallel
    175 particular focus
    176 patients
    177 pattern recognition techniques
    178 people
    179 perturbations
    180 physical activity
    181 population level
    182 pressure
    183 progression
    184 public health advice
    185 questions
    186 rare errors
    187 recognition techniques
    188 research
    189 resistance
    190 resonance spectroscopy
    191 response
    192 results
    193 risk
    194 risk of progression
    195 role
    196 scale
    197 scale studies
    198 sedentary lifestyle
    199 services
    200 side effects
    201 significant impact
    202 significant pressure
    203 single gene
    204 sites
    205 skeletal muscle
    206 small-molecule complement
    207 spectrometry
    208 spectrometry imaging
    209 spectroscopy
    210 statistics
    211 steatohepatitis
    212 storage
    213 storage of fat
    214 strong environmental interactions
    215 study
    216 subsequent T2DM
    217 subsequent obesity
    218 sugars
    219 summary
    220 technical summary
    221 technique
    222 temperature
    223 term use
    224 terms
    225 themes
    226 tissue
    227 tissue dysfunction
    228 tissue function
    229 tool
    230 transition
    231 type 2 diabetes
    232 use
    233 white adipose tissue
    234 white adipose tissue function
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