Biomarkers for Infant Fat Mass Development and Nutrition.
|Partner Organization||Partner Country|
|Erasmus Medical Center Rotterdam / Sophia Children's Hospital||The Netherlands|
|Technical University of Denmark, DTU||Denmark|
1. Overall project description
Childhood obesity is a rapidly growing problem in many countries across the world. Weight loss programs have limited effects and prevention is our only hope to stem this new epidemic. Development in the early life period has lifelong consequences. 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 healthy infants requires time, skilled personnel and specialized equipment, hence limiting implementation in routine neonatal care and research. Our hypothesis remains 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 currently found a range of lipids that show a strong association with body composition at different ages (3m, 12m and 24m).
We proposed that changes in infancy diet results in major changes in the infancy microbiome leading to altered metabolism of macronutrients, especially of lipids. Data on genetically caused differences in breastmilk oligosaccharides are strongly suggesting that the effect of the gut microbiome on lipid metabolism is occurring higher up in the intestinal tract than can be assessed by faecal microbiome analysis. Lipid ratio’s that reflect desaturase and elongase activity are predictive of growth and weight gain. We are therefore rapidly covering our aims:
The aims of this project were to:
1) Develop biomarkers for body fat distribution at 2 years of life;
A series of candidate biomarkers is currently under investigation and will be further validated.
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 usingdata from infants that receive both breast milk and formula (mixed feeding).
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. These results will be feed into a custom-designed integrative systems biology analyses which has been established. This allows the consortium to identify, substantiate and confirm biomarkers for fat distribution in this translational project that aims to provide new tools to help to prevent childhood obesity
Our work aims to develop biomarkers of body composition in babies and to predict childhood obestity. Our work has shown that the metabolite profile of infants at 3 months of age is predictive of their body compostion at 2 years. We are very excited about our current results, but we do not want release any details until we have been able to validate these findings.
We have also been able show that the gut microbiome at 3 months is strongly correlating with the lipid metabolism. Although it is difficult to determine cause and effect it is clear that the lipid metabolism and the gut microbiome are intertwined and that infant nurition and lifestyle therefore are crucial for the establisment of a healthy gut microbiome and healthy metabolism.
Further analysis is ongoing to validate these results across multiple cohorts.
4.1 List of publications
|Authors||Title||Year, Issue, PP||Partners Number||Doi|
|Furse S, Snowden SG*, Olga L, Prentice P, Ong KK, Hughes IA, Acerini CL, Dunger DB, Koulman A*.||Evidence from 3-month-old infants shows that a combination of postnatal feeding and exposures in utero shape lipid metabolism.||2019;9:14321||1||10.1038/s41598-019-50693-0||Download|
|Snowden SG*, Korosi A, de Rooij SR, Koulman A.*||Combining lipidomics and machine learning to measure clinical lipids in dried blood spots.||2020;16:83||1||10.1007/s11306-020-01703-0||Download|
|Snowden SG*, Fernandes HJR, Kent J, Foskolou S, Tate P, Field SF, Metzakopian E, Koulman A*.||Development and Application of High-Throughput Single Cell Lipid Profiling: A Study of SNCA-A53T Human Dopamine Neurons.||2020;23:101793||1||10.1016/j.isci.2020.101703||Download|
4.2 Presentation of the project
|Target group||Authors||Means of communication||Hyperlink|
4.3 List of submitted patents and other outputs
|Patent licence||Partners involved||Year||International eu or national patent||Comment|