HDHL-Biomarkers: Biomarkers for Infant Fat Mass Development and Nutrition (BioFN)
Lead Research Organisation:
University of Cambridge
Department Name: Clinical Biochemistry
Abstract
WHAT: Childhood obesity is a rapidly growing problem. Weight loss programs have limited effects and prevention is our only hope to stem this new epidemic. Infant fat mass development in particular, has long-term effects on later body fat mass and thus metabolic health. Lipid profiles may be used as biomarkers for fat mass development and provide predictive biomarkers for later childhood obesity.
WHO:
BioFN brings together experts on:
- Lipidomics (Dr Albert Koulman, University of Cambridge, UK);
- Paediatric endocrinology (Prof Anita Hokken-Koelega, Erasmus University, NL; Prof David Dunger and Dr Ken Ong, University of Cambridge, UK)
- Systems biology (Dr Henrik Bjoern Nielsen, Clinical Microbiomics, DK)
- Lipid metabolism (Dr Lars Hellgren, Danish Technical University, DK).
BioFN is coordinated by Dr Albert Koulman.
HOW:
BioFN will use high-resolution mass spectrometry based lipid profiling in samples from two birth cohort studies, Sophia-Pluto (Rotterdam, NL) and Cambridge Baby Growth Study (UK) that both have very precise body composition data. This will allow us to develop predictive biomarkers for fat distribution. By quantifying the dietary effect on lipid metabolism, gut microbiome metabolism and fat distribution BioFN will provide tools to prevent of childhood obesity.
WHO:
BioFN brings together experts on:
- Lipidomics (Dr Albert Koulman, University of Cambridge, UK);
- Paediatric endocrinology (Prof Anita Hokken-Koelega, Erasmus University, NL; Prof David Dunger and Dr Ken Ong, University of Cambridge, UK)
- Systems biology (Dr Henrik Bjoern Nielsen, Clinical Microbiomics, DK)
- Lipid metabolism (Dr Lars Hellgren, Danish Technical University, DK).
BioFN is coordinated by Dr Albert Koulman.
HOW:
BioFN will use high-resolution mass spectrometry based lipid profiling in samples from two birth cohort studies, Sophia-Pluto (Rotterdam, NL) and Cambridge Baby Growth Study (UK) that both have very precise body composition data. This will allow us to develop predictive biomarkers for fat distribution. By quantifying the dietary effect on lipid metabolism, gut microbiome metabolism and fat distribution BioFN will provide tools to prevent of childhood obesity.
Technical Summary
Development in the early life period has lifelong consequences. Accelerated postnatal weight gain is associated with an adverse metabolic profile and increased obesity risk in adulthood. Height and weight gain are only crude measures and do not take body composition into account. Early visceral fat mass development, in particular, is thought to have long-term effects on later body fat mass and fat distribution, and thus metabolic health. Accurate measurements of fat mass development in infants requires time, skilled personnel and equipment, hence limiting use in routine neonatal care and research.
Our hypothesis is that the differences in fat mass development are associated with differences in lipid metabolism, which are driven by diet and gut microbiome activity in response to diet. We propose that changes in infancy diet results in major changes in the infancy microbiome leading to altered metabolism of macronutrients, especially of lipids. Lipid profiles could be used as biomarkers for fat mass development, microbiome metabolism and reflect growth trajectories. Our aims are to:
1) Develop biomarkers for body fat distribution at 2 years of life;
2) Develop lipid-based biomarkers at an early age to predict body fat distribution at 2 years of age;
3) Develop predictive biomarkers for later childhood (5-10 years) body composition (lean vs. fat) and adipose tissue distribution (subcutaneous vs. visceral);
4) Quantify the dietary effect on lipid metabolism, gut microbiome metabolism and fat distribution using data from infants that receive both breast milk and formula.
Existing detailed anthropometric and food intake data of healthy term infants from the Sophia-Pluto cohort will be combined with extensive lipidomic profiling and data from the BBSRC-DRINC project. This will feed into a custom designed integrative systems biology analyses enabling this consortium to identify, substantiate and confirm biomarkers for fat distribution in this translational project.
Our hypothesis is that the differences in fat mass development are associated with differences in lipid metabolism, which are driven by diet and gut microbiome activity in response to diet. We propose that changes in infancy diet results in major changes in the infancy microbiome leading to altered metabolism of macronutrients, especially of lipids. Lipid profiles could be used as biomarkers for fat mass development, microbiome metabolism and reflect growth trajectories. Our aims are to:
1) Develop biomarkers for body fat distribution at 2 years of life;
2) Develop lipid-based biomarkers at an early age to predict body fat distribution at 2 years of age;
3) Develop predictive biomarkers for later childhood (5-10 years) body composition (lean vs. fat) and adipose tissue distribution (subcutaneous vs. visceral);
4) Quantify the dietary effect on lipid metabolism, gut microbiome metabolism and fat distribution using data from infants that receive both breast milk and formula.
Existing detailed anthropometric and food intake data of healthy term infants from the Sophia-Pluto cohort will be combined with extensive lipidomic profiling and data from the BBSRC-DRINC project. This will feed into a custom designed integrative systems biology analyses enabling this consortium to identify, substantiate and confirm biomarkers for fat distribution in this translational project.
Planned Impact
Need for innovation: It is well established that early life growth trajectories are associated with later life body composition and metabolic health. The mechanisms responsible for body composition development in infancy and early childhood remain largely unknown. Also, effects of infant feeding on growth trajectories are poorly defined. Progress in this field of research is hampered by the complexity and costs of body composition measurements in young infants and children. Validated biochemical marker patterns for healthy growth and fat mass development would reduce study time, the number of participants and total research costs. This work will make it easier for future academic and industrial studies to investigate effects of different nutrients and nutritional compositions on growth, development, and long-term health.
Relevance for public health: Better and personalized feeding strategies for infants will provide a healthier start of life and therefore reduce their risk of childhood obesity and related disease in later life. This will have a significant impact on future health care costs throughout the life course by reducing the incidence of obesity and metabolic diseases. The BioFN project will explore the clinical application of lipid biomarkers for body fat distribution. With the current surge in childhood obesity and the necessity to act on prevention rather than focussing on weightloss, it is essential to have access to predictive biomarkers. Detailed body fat distribution measurements are not possible in a routine health care, which in many European countries takes place at home. Biomarkers for fat distribution that can be measured from dried blood spots means that almost all infants can be assessed and early prevention of further development of childhood obesity addressed.
Long term aims of the consortium: The clinical application of the biomarkers that we aim to develop in this work will be the hallmark of success for this project. However, it is important to have a realistic view on the timelines of biomarker development validation and clinical application, and moving from differential biomarkers to clinical application, often takes more than 10 years (Koulman et al. 2009). We, therefore, expect that this project will be the first step on this long path. During the second year of the project, we expect to have data showing how strongly these biomarkers can predict fat distribution and later childhood obesity. This will then be used to apply for follow-up funding to start a translational project, with the aim to first validate the findings and further test how changes in diet and behaviour can affect these biomarkers. In addition, the multidisciplinary consortium opens new avenues to extend the strategic international collaboration to better understand the interaction between infancy diet (both milk and weaning foods in young children), adiposity development and lifelong metabolic implications. It allows for follow-up projects including nutritional intervention studies, with the ultimate goal to improve the nutritional quality of infant milks and foods.
Childhood obesity is a rapidly growing problem in many countries across the world. With the limited effect of treatment, prevention is our only hope to stem this new epidemic. Early biomarkers that can predict childhood obesity and early targeted interventions that can improve healthy fat distribution in infants are needed, which underlines the urgency of the BioFN project.
Relevance for public health: Better and personalized feeding strategies for infants will provide a healthier start of life and therefore reduce their risk of childhood obesity and related disease in later life. This will have a significant impact on future health care costs throughout the life course by reducing the incidence of obesity and metabolic diseases. The BioFN project will explore the clinical application of lipid biomarkers for body fat distribution. With the current surge in childhood obesity and the necessity to act on prevention rather than focussing on weightloss, it is essential to have access to predictive biomarkers. Detailed body fat distribution measurements are not possible in a routine health care, which in many European countries takes place at home. Biomarkers for fat distribution that can be measured from dried blood spots means that almost all infants can be assessed and early prevention of further development of childhood obesity addressed.
Long term aims of the consortium: The clinical application of the biomarkers that we aim to develop in this work will be the hallmark of success for this project. However, it is important to have a realistic view on the timelines of biomarker development validation and clinical application, and moving from differential biomarkers to clinical application, often takes more than 10 years (Koulman et al. 2009). We, therefore, expect that this project will be the first step on this long path. During the second year of the project, we expect to have data showing how strongly these biomarkers can predict fat distribution and later childhood obesity. This will then be used to apply for follow-up funding to start a translational project, with the aim to first validate the findings and further test how changes in diet and behaviour can affect these biomarkers. In addition, the multidisciplinary consortium opens new avenues to extend the strategic international collaboration to better understand the interaction between infancy diet (both milk and weaning foods in young children), adiposity development and lifelong metabolic implications. It allows for follow-up projects including nutritional intervention studies, with the ultimate goal to improve the nutritional quality of infant milks and foods.
Childhood obesity is a rapidly growing problem in many countries across the world. With the limited effect of treatment, prevention is our only hope to stem this new epidemic. Early biomarkers that can predict childhood obesity and early targeted interventions that can improve healthy fat distribution in infants are needed, which underlines the urgency of the BioFN project.
People |
ORCID iD |
Albert Koulman (Principal Investigator) |
Publications
Snowden SG
(2020)
Development and Application of High-Throughput Single Cell Lipid Profiling: A Study of SNCA-A53T Human Dopamine Neurons.
in iScience
Mann JP
(2022)
Comparison of the Lipidomic Signature of Fatty Liver in Children and Adults: A Cross-Sectional Study.
in Journal of pediatric gastroenterology and nutrition
Stanley EG
(2017)
Lipidomics Profiling of Human Adipose Tissue Identifies a Pattern of Lipids Associated with Fish Oil Supplementation.
in Journal of proteome research
Murfitt SA
(2018)
Metabolomics and Lipidomics Study of Mouse Models of Type 1 Diabetes Highlights Divergent Metabolism in Purine and Tryptophan Metabolism Prior to Disease Onset.
in Journal of proteome research
Harshfield EL
(2019)
An Unbiased Lipid Phenotyping Approach To Study the Genetic Determinants of Lipids and Their Association with Coronary Heart Disease Risk Factors.
in Journal of proteome research
Kasim HH
(2023)
A comparative analyses of lipid ratios representing desaturase enzyme activity between preterm and term infants within the first ten weeks of life.
in Lipids in health and disease
Snowden SG
(2020)
Combining lipidomics and machine learning to measure clinical lipids in dried blood spots.
in Metabolomics : Official journal of the Metabolomic Society
Bond NJ
(2017)
massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics.
in Metabolomics : Official journal of the Metabolomic Society
Furse S
(2022)
Paternal nutritional programming of lipid metabolism is propagated through sperm and seminal plasma.
in Metabolomics : Official journal of the Metabolomic Society
Description | We have developed a set of metabolites that are can serve as blood based biomarkers of future body composition. Our results show that metabolic profile of children 3 months are predictive of body composition at 2 years of age. Further work is necessary to determine if lifestyle intervention between 3 months and 2 years are able to change these outcomes. |
Exploitation Route | This is ongoing |
Sectors | Agriculture Food and Drink Pharmaceuticals and Medical Biotechnology |
Description | Children's Liver Disease Foundation funding |
Amount | £5,101 (GBP) |
Organisation | Children's Liver Disease Foundation (CLDF) |
Sector | Academic/University |
Country | United Kingdom |
Start | 11/2017 |
End | 10/2018 |
Description | MRC Confidence in Global Nutrition and Health Research Initiative |
Amount | £53,900 (GBP) |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 01/2018 |
End | 01/2019 |
Description | Michael J Fox Foundation Biomarkers Fall 2018 |
Amount | $500,000 (USD) |
Funding ID | not yet given |
Organisation | Michael J Fox Foundation |
Sector | Charity/Non Profit |
Country | United States |
Start | 03/2019 |
End | 02/2021 |
Description | Wellcome Nutrition Award |
Amount | £49,948 (GBP) |
Funding ID | 215852/Z/19/Z |
Organisation | Wellcome Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2019 |
End | 02/2020 |
Description | Dutch Famine Cohort |
Organisation | University of Amsterdam |
Department | Swammerdam Institute for Life Sciences |
Country | Netherlands |
Sector | Academic/University |
PI Contribution | Collaboration on the effect of famine during pregnancy on lipid metabolism |
Collaborator Contribution | Amsterdam provide samples of the cohort |
Impact | The collaboration aims to understand the effect of prenatal famine on lifelong lipid metabolism |
Start Year | 2017 |
Description | High-throughput single cell unbiased lipidomics assay in human iPSC-derived dopamine neurons. |
Organisation | University of Cambridge |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | The development of single cell lipidomics approaches to study the lipid metabolism of dopageneric neurons in relation to parkinson's disease |
Collaborator Contribution | Changes in lipid metabolism have been strongly associated with Parkinson's disease (PD). Lipids have the potential to be important biomarkers for PD, but the lack of appropriate tools to measure total lipids (lipidome) in human dopamine neurons has limited advances in this field. Here, we propose to develop a novel unbiased and high-throughput single cell assay to determine total lipids. This will allow us to identify and validate lipid metabolites in dopamine neurons, which may serve as biomarkers for PD. |
Impact | project is ongoing |
Start Year | 2019 |
Description | Understanding Society Health Innovation Panel: Biomeasure And Health Data Collection From The Innovation Panel Of The Uk Household Longitudinal Study |
Organisation | University of Essex |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | The measurement of biomarkers in dried blood spots |
Collaborator Contribution | Organise the dried blood spot collection and other data collection |
Impact | still in progress |
Start Year | 2019 |
Description | bibins |
Organisation | Queen Mary University of London |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | To collaborate on the BiBins study |
Collaborator Contribution | providing samples of the Bibins cohort |
Impact | samples have been analysed, data analysis is in progress |
Start Year | 2017 |
Description | Participated in LifeLab Peterborough |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Public/other audiences |
Results and Impact | Using the Fortune telling molecules to explain nutritional biomarkers. |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.camlifelab.co.uk/peterborough |
Description | The Fortune Telling Molecules, explaining nuritional biomarkers to the audience of the Einstein's Garden at the Green man Festivel |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | Over 4 days we have spoken to hunderts of people about nutritional biomarkers and got them involved in a hands-on activity. |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.greenman.net/news/discover-whats-landing-in-einsteins-garden/ |