Poster Presentation Australian and New Zealand Obesity Society Annual Scientific Conference 2026

Identifying biomarkers for adverse neonatal outcomes in women with metabolic dysfunction using discovery proteomics (#118)

Xian Ho 1 2 , Matilda S G Longfield 1 2 3 , Amanda R Purcell 1 2 , Daniel Kim 4 , Natassia Rodrigo 3 , Kushalee Jayawickreme 1 3 , Jean Yang 4 , Sarah J Glastras 1 2 3
  1. Kolling Institute of Medical Research, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, Australia
  2. Northern Precinct, Sydney Medical School, University of Sydney, Camperdown, NSW, Australia
  3. Department of Diabetes, Metabolism and Endocrinology, Royal North Shore Hospital, St Leonards, NSW, Australia
  4. School of Mathematics, University of Sydney, Camperdown, NSW, Australia

Background: The prevalence of metabolic conditions in women of reproductive age is steadily increasing. Despite extensive evidence that these women are at greater risk of adverse neonatal outcomes, irrespective of gestational diabetes mellitus (GDM) development, there are currently limited tools to identify which women are at greatest risk and may benefit from targeted interventions beyond standard antenatal care. Proteomics represents a powerful but underutilised method for high-throughput, unbiased discovery of novel biomarkers.

Aim: To identify biomarker candidates for adverse neonatal outcomes from maternal serum in women with metabolic dysfunction using a discovery proteomics approach.  

Methods: In pregnant women with known metabolic risk factors that did not develop GDM, serum proteins were analysed using data-independent acquisition liquid chromatography-mass spectrometry and identified by Spectronaut using UniProt IDs. Exploratory bivariate analyses and multivariate logistic regressions were performed to investigate whether clinical risk factors, pathology results, and proteins were significantly associated with a predetermined composite neonatal outcome independent of iatrogenic choice (large for gestational age, respiratory distress, jaundice above treatment threshold, hypoglycaemia, and perinatal death). Predictive utility of each model was compared using model fit and discrimination.

Results: 99 women were included, of whom 46% experienced the composite outcome. Clinical risk factors and pathology showed no significant associations, while 16 proteins were significantly associated with increased odds of adverse neonatal outcomes (p<0.05). Pathway analysis revealed functionally relevant links to placental lactogen, endopeptidase inhibition, and complement and coagulation pathways that have previously been implicated in maternal obesity, GDM, and pre-eclampsia. 22 panels of between 7 and 11 proteins demonstrated strong fit and discrimination within the study population.

Conclusion: Maternal serum proteins show early promise as potential biomarkers for identifying women with metabolic dysfunction at greatest risk of adverse neonatal outcomes for preventative care. These exploratory findings merit external validation in larger and more heterogenous cohorts.