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NewbornsInSA multi-omic newborn screening: protocol for a prospective cohort study.

Lucy Anastasi¹, Ayesha Chowdhury¹, Alex Ashenden^1,2

¹Department of Genetics and Molecular Pathology, SA Pathology, Adelaide, South Australia, Australia.

|March 11, 2026

Summary

This study introduces a new multi-omic newborn screening model integrating metabolomics and genomics. This approach aims to identify more treatable childhood conditions earlier, improving infant health outcomes.

Keywords:

GENETICS Genomic Medicine Mass Screening PAEDIATRICS PUBLIC HEALTH Preventive Health Services

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Area of Science:

Genetics
Metabolomics
Public Health

Background:

Current newborn bloodspot screening (NBS) in Australia screens ~300,000 infants annually for ~30 conditions.
Existing NBS relies on mass spectrometry, limiting detection to specific biomarkers.
Advancements in metabolomics and genomics offer potential to screen for hundreds more treatable conditions.

Purpose of the Study:

To develop, validate, and evaluate a novel multi-omic newborn screening model.
To integrate metabolomic and genomic screening methodologies for expanded condition detection.
To assess the acceptability, feasibility, and cost-effectiveness of this integrated approach.

Main Methods:

Recruiting 1000 families for genomic NBS (whole-genome sequencing, 600+ gene panel) and metabolomic screening.
Reporting clinically actionable genetic variants to parents.
Evaluating program acceptability via stakeholder engagement and family surveys.
Assessing diagnostic yield, accuracy, costs, and consequences against standard NBS.

Main Results:

Hypothesizes increased condition identification and reduced time to diagnosis.
Anticipates earlier care and improved outcomes for newborns with genetic conditions.
Aims to demonstrate the feasibility and cost-effectiveness of multi-omic NBS.

Conclusions:

The multi-omic newborn screening model holds promise for earlier and broader detection of childhood conditions.
This integrated approach could significantly improve diagnostic timelines and patient outcomes.
Further research and validation are essential for clinical implementation.