Velden, Monique G.M. de Sain–van der

Newborn screening (NBS) for inborn errors of metabolism is challenged by high false-positive rates, which may lead to parental anxiety and increased healthcare costs associated with diagnostic follow-up. False-positive results often arise from changes in metabolite concentrations that mimic metabolic disorders as a consequence of differences in perinatal factors or nutritional status. To address this, Collaborative Laboratory Integrative Reports (CLIR) and the associated post-analytical tools (PATs) using multivariate interpretation and covariate-adjusted reference intervals may be used to improve specificity of NBS algorithms. In the current study, we examined whether CLIR can be applied to optimize the Dutch NBS program by reducing the false-positive rates. We developed and validated a CLIR-based PAT for CPT1 deficiency, GA-I, IVA and MSUD within the Dutch NBS program. Single-condition tools (SCTs) and multivariate approaches, including marker ratios and covariate adjustments, were evaluated for their ability to discriminate true- and false-positive referrals. For CPT1 deficiency, age-adjusted SCT combined with birthweight, location correction, and the C18:1/methionine ratio substantially reduced false positives. For GA-I, C3DC-based ratios improved specificity while preserving true-positive detection, potentially reflecting postnatal renal immaturity in some cases. For IVA, the dual scatter plot fully separated true- and false-positive referrals, highlighting the limitations of single-marker screening. For MSUD, differences between false-positive and true-positive cases were more pronounced, yet a similar number of false positives were still referred; valine-related markers contributed to false positives, while leucine and the Xle/Phe ratio better identified true positives. CLIR-based post-analytical tools enhanced NBS specificity through covariate-aware, multivariate interpretation. This provides important input for decision makers in both the Dutch NBS, as well as the NBS community worldwide.

Since October 2019, screening for methylmalonic acidemia (MMA) has been implemented in the Dutch Newborn Screening (NBS) program. Since implementation, most referrals for MMA have been the result of (maternal) vitamin B12 deficiency. Although vitamin B12 deficiency is an important condition and early detection can confer health benefits, its identification was not the original objective of the screening. We therefore examined whether genetic forms of MMA can be distinguished from acquired forms. Early distinction between these forms is essential for guiding clinical management, informing prognosis, and enabling appropriate genetic counseling. Specifically, we tested whether the use of Collaborative Laboratory Integrated Reports (CLIR) to complement NBS results improved specificity of the test for genetic MMAs. We found that with the use of CLIR, genetic conditions including methylmalonyl-CoA mutase (mut) deficiency and cobalamin (cbl) A, B, C and D deficiency can be partially differentiated from acquired causes. This results in a significant reduction in the number of second-tier tests required. However, this approach may also exclude certain other genetic causes. Based on all findings, we provide considerations and implications for MMA screening that may inform decision-makers in (other) NBS programs.

Background/Objectives: Dutch newborn screening is an important public health program designed to detect conditions early in life, enabling timely interventions that can prevent mortality, morbidity, and long-term disabilities. However, the program also faces certain challenges. One such issue is obtaining and maintaining a high positive predictive value (PPV); another is that newborn screening (NBS) in the Netherlands is intended for all newborn babies until the age of six months. This means comparing infants at different ages may introduce variability that complicates data interpretation. To support the optimization of the program, we systematically analyzed population-level tandem mass spectrometry (MS/MS) data to explore postnatal metabolic changes. Methods: We evaluated the impact of covariates—including birth weight, gestational age, age at blood collection, and biological sex—on metabolite profiles using retrospective newborn screening (NBS) data. Special emphasis was placed on the combined effects of these covariates. The analysis was based on data from 985,629 newborns collected between 2018 and 2024. Results: Specifically, (extremely) preterm infants exhibit altered levels of several amino acids and acylcarnitines. Moreover, we observed multiplicative effects of gestational age and birth weight on several metabolic markers. Biological sex however, does not have an impact. The largest impact of the age of sampling was observed on the C0/C16+C18 ratio, which may impact screening performance for CPT1 deficiency. Conclusions: Covariate-adjusted reference values could improve the performance of the Dutch newborn screening.