A New Approach to Objectively Evaluate Inherited Metabolic Diseases for Inclusion on Newborn Screening Programmes

Area of Science:

• Medical Genetics
• Public Health
• Biochemistry

Background:

• Newborn screening (NBS) is crucial for diagnosing inherited metabolic diseases (IMDs) and enabling early treatment.
• Current NBS criteria (WHO) are inconsistently applied across European countries, leading to screening disparities.
• Advances in diagnostics and therapeutics necessitate updated, evidence-based approaches to NBS expansion.

Purpose of the Study:

• To develop a novel, objective algorithm for assessing and prioritizing IMDs for inclusion in NBS programs.
• To provide a standardized framework for evaluating potential new NBS targets.
• To facilitate the expansion of NBS programs based on robust scientific criteria.

Main Methods:

• Developed a point-based algorithm founded on classic Wilson and Jungner screening principles.
• Structured the algorithm around three core pillars: condition, screening, and treatment.
• Validated the algorithm using six IMDs currently included in the UK's NBS program.

Main Results:

• The algorithm generates a weight-based score for IMDs.
• This score serves as an initial step in evaluating disorders for NBS inclusion.
• The system objectively prioritizes conditions for further assessment.

Conclusions:

• The proposed algorithm offers a robust method for prioritizing IMDs in NBS program development.
• It addresses the need for objective, measurable criteria in expanding NBS.
• This tool can assist countries in making informed decisions about NBS program composition.