University of Cambridge
Study of Fat Metabolism and the Interplay with Insulin in Preterm Infants in the First Year of Life
Abstract
dc:description.abstractPreterm infants (PIs) face a higher risk of chronic morbidity in adulthood, including cardiovascular diseases, and Diabetes Mellitus type 1 and type 2. The underlying causal mechanisms, whether driven by pre- or postnatal factors, remain obscure. Although this risk is well-known, its mechanism and tools for early detection, particularly for identifying metabolic alterations and insulin resistance, remain sparse. This research specifically addresses these gaps by determining the impact of prematurity on lipid metabolism and evaluating its interplay with insulin sensitivity during the first year of life. The methodological approach is structured around the research objectives and involves three main studies. For lipid metabolism, the study observed PIs (<34 weeks of gestation at birth) at Rosie Hospital in Cambridge (Primrose) and compared them with term infants from the Cambridge Baby Growth Study-Breast Feeding (CBGS-BF) at equivalent age. Dried blood spots (DBS) samples were collected and analysed for lipid metabolism using high performance - liquid chromatography mass spectrometry (HP-LCMS) at four timepoints and the analytical work is presented in Chapter 4. The ratio of specific relative lipid abundances (RLA) from the early preterm (EP) study, Primrose and CBGS-BF cohorts was calculated to estimate desaturase enzyme activity since the first 10 weeks of life until 12 months corrected age and published in Chapter 5. In Chapter 6, C-peptide concentrations-derived from DBS and plasma samples were compared, and the C-peptide concentrations were used to estimate insulin sensitivity indices (HOMA2-IR, HOMA2-IS and HOMA2-%B). Continuous glucose monitoring (CGM) data obtained from PIs at-term-corrected-age (TCA) were used to predict insulin sensitivity indices, as presented in Chapter 7. The impact of insulin sensitivity on the lipidome in PIs is demonstrated in Chapter 8. Finally, Chapter 9 describes a translational study of ovine model, with lipidome analyses performed on blood samples from fetal sheep assigned to control, progesterone and dexamethasone cohorts. iv Key findings include distinct lipid trends in PIs, characterised by divergent trajectories across multiple sphingomyelin (SM), phosphatidylcholine (PC) and triglycerides (TG) lipid species and Δ5 desaturase (D5D) enzyme activity, which were significantly affected by age and weight parameters. Elevated HOMA2-IR significantly suppressed SM lipids (Linear Mixed Model (LMM) analysis, p<0.0003). In the ovine model, dexamethasone administration suppressed SM and cholesterol ester (CE) abundances, although these effects were indistinguishable from those induced by progesterone. The CGM-based model at TCA generated a predictive formula for HOMA2-IR (r=0.91, p<0.001, LMM analysis). In conclusion, this study provides comprehensive characterisations of lipid alterations in PIs across multiple timepoints, influenced by prematurity, growth parameters and insulin sensitivity. This research introduces two novel clinical monitoring approaches: (1) the identification of specific lipid biomarkers that may serve as early indicators of metabolic dysregulation in PIs, and (2) a CGM-based prediction model for HOMA2-IR at TCA. These findings offer non-invasive and clinically feasible tools for a better understanding of distinct metabolic challenges faced by PIs from early life and the potential to improve dietary and monitoring interventions aimed at anticipating long-term health outcomes.
Degree
thesis:*- Name dc:type.qualificationname
- Doctor of Philosophy (PhD)
- Level dc:type.qualificationlevel
- Doctoral
- Grantor dc:publisher.institution
- University of Cambridge
- Year dc:date.issued
- 2025
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Kasim, Hanis Hidayu
- Advisor dc:contributor.advisor
-
- Beardsall, Kathryn
Subjects
dc:subject × 5Rights
dc:rightsIdentifiers
dc:identifier.*- DOI dc:identifier.doi
- https://doi.org/10.17863/CAM.121880
- OAI identifier oai:identifier
- oai:www.repository.cam.ac.uk:1810/390275