Development of Second-Tier Liquid Chromatography-Tandem Mass Spectrometry Analysis for Expanded Newborn Screening in Japan

Current Status of Newborn Bloodspot Screening Worldwide 2024: A Comprehensive Review of Recent Activities (2020-2023)

Newborn bloodspot screening (NBS) began in the early 1960s based on the work of Dr. Robert "Bob" Guthrie in Buffalo, NY, USA. His development of a screening test for phenylketonuria on blood absorbed onto a special filter paper and transported to a remote testing laboratory began it all. Expansion of NBS to large numbers of asymptomatic congenital conditions flourishes in many settings while it has not yet been realized in others. The need for NBS as an efficient and effective public health prevention strategy that contributes to lowered morbidity and mortality wherever it is sustained is well known in the medical field but not necessarily by political policy makers. Acknowledging the value of national NBS reports published in 2007, the authors collaborated to create a worldwide NBS update in 2015. In a continuing attempt to review the progress of NBS globally, and to move towards a more harmonized and equitable screening system, we have updated our 2015 report with information available at the beginning of 2024. Reports on sub-Saharan Africa and the Caribbean, missing in 2015, have been included. Tables popular in the previous report have been updated with an eye towards harmonized comparisons. To emphasize areas needing attention globally, we have used regional tables containing similar listings of conditions screened, numbers of screening laboratories, and time at which specimen collection is recommended. Discussions are limited to bloodspot screening.

A newborn Screening Programme for Inborn errors of metabolism in Galicia: 22 years of evaluation and follow-up

BACKGROUND

There is a notable lack of harmonisation in newborn screening (NBS) programmes worldwide. The Galician programme for early detection of inborn errors of metabolism (IEM) was one of the first NBS programmes in Europe to incorporate mass spectrometry (July 2000). This programme currently screens for 26 IEMs in dried blood and urine samples collected 24-72 h after birth.

RESULTS

In its 22-year history, this programme has analysed samples from 440,723 neonates and identified 326 cases of IEM with a prevalence of 1:1351. The most prevalent IEMs were hyperphenylalaninaemia (n = 118), followed by medium chain acyl-CoA dehydrogenase deficiency (MCADD, n = 26), galactosaemia (n = 20), and cystinurias (n = 43). Sixty-one false positives and 18 conditions related to maternal pathologies were detected. Urine samples have been identified as a useful secondary sample to reduce the rate of false positives and identify new defects. There were 5 false negatives. The overall positive value was 84.23%. The fatality rate over a median of 12.1 years of follow-up was 2.76%. The intelligence quotient of patients was normal in 95.7% of cases, and school performance was largely optimal, with pedagogic special needs assistance required in < 10% of cases. Clinical onset of disease preceded diagnosis in 4% of cases. The age at which first NBS report is performed was reduced by 4 days since 2021.

CONCLUSIONS

This study highlights the benefits of collecting urine samples, reduce NBS reporting time and expanding the number of IEMs included in NBS programmes.

Analysis of a second-tier test panel in dried blood spot samples using liquid chromatography-tandem mass spectrometry in Catalonia's newborn screening programme

OBJECTIVES

Acylcarnitine and amino acid analyses of dried blood spot (DBS) samples using tandem mass spectrometry in newborn screening (NBS) programmes can generate false positive (FP) results. Therefore, implementation of second-tier tests (2TTs) using DBS samples has become increasingly important to avoid FPs. The most widely used 2TT metabolites include methylmalonic acid, 3-hydroxypropionic acid, methylcitric acid, and homocysteine.

METHODS

We simultaneously measured 46 underivatised metabolites, including organic acids, acylglycine and acylcarnitine isomers, homocysteine, and orotic acid, in DBS samples using tandem mass spectrometry. To validate this method, we analysed samples from 147 healthy newborns, 160 patients with genetic disorders diagnosed via NBS, 20 patients with acquired vitamin B12 deficiency, 10 newborns receiving antibiotic treatment, and nine external quality control samples.

RESULTS

The validation study revealed that 31 metabolites showed good analytical performance. Furthermore, this method detected key metabolites for all diseases associated with increased levels of the following acylcarnitines: C3, C4, C5, C4DC/C5OH, and C5DC. The sensitivity of this method to detect all diseases was 100 %, and the specificity was 74-99 %, except for glutaric aciduria type 1. This method can also be used to diagnose mitochondrial fatty acid β-oxidation disorders (FAODs) and urea cycle defects (UCDs).

CONCLUSIONS

We have described a 2TT panel of 31 metabolites in DBS samples based on an easy and rapid method without derivatisation. Its implementation allowed us to distinguish between different organic acidurias, some FAODs, and UCDs. This new strategy has increased the efficiency of our NBS programme by reducing FP and false negative results, second sample requests, and the time required for diagnosis.

Butyrylcarnitine Elevation in Newborn Screening: Reducing False Positives and Distinguishing between Two Rare Diseases through the Evaluation of New Ratios

One of the main challenges of newborn screening programs, which screen for inherited metabolic disorders, is cutting down on false positives (FPs) in order to avoid family stresses, additional analyses, and unnecessary costs. False positives are partly caused by an insubstantial number of robust biomarkers in evaluations. Another challenge is how to distinguish between diseases which share the same primary marker and for which secondary biomarkers are just as highly desirable. Focusing on pathologies that involve butyrylcarnitine (C4) elevation, such as short-chain acylCoA dehydrogenase deficiency (SCADD) and isobutyrylCoA dehydrogenase deficiency (IBDD), we investigated the acylcarnitine profile of 121 newborns with a C4 increase to discover secondary markers to achieve two goals: reduce the FP rate and discriminate between the two rare diseases. Analyses were carried out using tandem mass spectrometry with whole blood samples spotted on filter paper. Seven new biomarkers (C4/C0, C4/C5, C4/C5DC\C6OH, C4/C6, C4/C8, C4/C14:1, C4/C16:1) were identified using a non-parametric ANOVA analysis. Then, the corresponding cut-off values were found and applied to the screening program. The seven new ratios were shown to be robust (p < 0.001 and p < 0.01, 0.0937 < ε2 < 0.231) in discriminating between FP and IBDD patients, FP and SCADD patients, or SCADD and IBDD patients. Our results suggest that the new ratios are optimal indicators for identifying true positives, distinguishing between two rare diseases that share the same primary biomarker, improving the predictive positive value (PPV) and reducing the false positive rate (FPR).

Characteristics, differential diagnosis, individualized treatment, and prevention of hyperhomocysteinemia in newborns

OBJECTIVES

This study aimed to investigate the incidence rate, clinical phenotype, gene variation spectrum, and prognosis of neonatal hyperhomocysteinemia (HHcy) and explore its diagnosis, individualised treatment, and prevention strategies.

METHODS

We screened 84722 neonates for HHcy using liquid chromatography-tandem mass spectrometry (LC-MS/MS) combined with biochemical detection, urine gas chromatography-mass spectrometry (GC-MS), and next-generation sequencing (NGS) for gene analysis to comprehensively differentiate and diagnose diseases.

RESULTS

18 children (P1-P18) were diagnosed with methylmalonic acidemia (MMA) and HHcy, and fourteen known and one new variant of the MMACHC gene were found. Five children showed poor mental reactions, brain dysplasia, lethargy, hyperbilirubinemia, and jaundice, whereas the other 13 children had no evident abnormalities. These children were all cobalamin- and folic acid-reactive types, and they were mainly supplemented with cobalamin, L-carnitine, betaine, and folic acid. The mother of P12 had a prenatal diagnosis at the next pregnancy; the results showed that MMACHC gene was not pathogenic and she gave birth to a healthy baby. One child (P19) was diagnosed with methylenetetrahydrofolate reductase (MTHFR) deficiency, and one new mutation was detected in the MTHFR gene. Patient P19 showed congenital brain dysplasia, neonatal anaemia, and hyperbilirubinemia, and treatment consisted mainly of betaine and cobalamin supplementation. One child (P20) was confirmed to have methionine adenosyltransferase I (MAT I) deficiency but had no clinical manifestations. After treatment, all the children had a good prognosis.

CONCLUSION

The incidence of neonatal HHcy in the Zibo area was 1/4236, and the common pathogenic variants were c.609G>A, c.80A>G, and c.482G>A in the MMACHC gene. Patients with HHcy can achieve a good prognosis if pathogenic factors and targeted treatment are identified. Gene analysis and prenatal diagnosis contribute to the early prevention of HHcy.

Validation of a targeted metabolomics panel for improved second-tier newborn screening

Improved second-tier assays are needed to reduce the number of false positives in newborn screening (NBS) for inherited metabolic disorders including those on the Recommended Uniform Screening Panel (RUSP). We developed an expanded metabolite panel for second-tier testing of dried blood spot (DBS) samples from screen-positive cases reported by the California NBS program, consisting of true- and false-positives from four disorders: glutaric acidemia type I (GA1), methylmalonic acidemia (MMA), ornithine transcarbamylase deficiency (OTCD), and very long-chain acyl-CoA dehydrogenase deficiency (VLCADD). This panel was assembled from known disease markers and new features discovered by untargeted metabolomics and applied to second-tier analysis of single DBS punches using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in a 3-min run. Additionally, we trained a Random Forest (RF) machine learning classifier to improve separation of true- and false positive cases. Targeted metabolomic analysis of 121 analytes from DBS extracts in combination with RF classification at a sensitivity of 100% reduced false positives for GA1 by 83%, MMA by 84%, OTCD by 100%, and VLCADD by 51%. This performance was driven by a combination of known disease markers (3-hydroxyglutaric acid, methylmalonic acid, citrulline, and C14:1), other amino acids and acylcarnitines, and novel metabolites identified to be isobaric to several long-chain acylcarnitine and hydroxy-acylcarnitine species. These findings establish the effectiveness of this second-tier test to improve screening for these four conditions and demonstrate the utility of supervised machine learning in reducing false-positives for conditions lacking clearly discriminating markers, with future studies aimed at optimizing and expanding the panel to additional disease targets.

Identification of potential interferents of methylmalonic acid: A previously unrecognized pitfall in clinical diagnostics and newborn screening

OBJECTIVES

Determination of methylmalonic acid (MMA) from dried blood spots (DBS) is commonly performed in clinical diagnostics and newborn screening for propionic acidemia (PA) and methylmalonic acidemia. Isobaric compounds of MMA having the same mass can affect diagnostic reliability and quantitative results, which represents a previously unrecognized pitfall in clinical assays for MMA. We set out to identify interfering substances of MMA in DBS, serum and urine samples from confirmed patients with PA and methylmalonic acidemia.

METHODS

Techniques included quadrupole time-of-flight high-resolution mass spectrometry (QTOF HR-MS), nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography (LC) and tandem mass spectrometry (MS/MS).

RESULTS

The five isobaric metabolites detected in DBS, serum and urine from PA and methylmalonic acidemia patients were confirmed as 2-methyl-3-hydroxybutyrate, 3-hydroxyisovalerate, 2-hydroxyisovalerate, 3-hydroxyvalerate and succinate using a series of experiments. An additional unknown substance with low abundance remained unidentified.

CONCLUSIONS

The presented results facilitate the diagnostic and quantitative reliability of the MMA determination in clinical assays. Isobaric species should be investigated in assays for MMA to eliminate possible interference in a wide range of conditions including PA, methylmalonic acidemia, a vitamin B₁₂ deficiency, ketosis and lactic acidosis.

Incorporation of second-tier tests and secondary biomarkers to improve positive predictive value (PPV) rate in newborn metabolic screening program

Background

Nowadays, neonatal screening has become an essential part of routine newborn care in the world. This is a non‐invasive evaluation that evaluated inborn errors of metabolisms (IEMs) using tandem mass spectrometry (LC‐MS/MS) for the evaluation of the baby's risk of certain metabolic disorders.

Methods

This retrospective study was conducted on 39987 Iranian newborns who were referred to Nilou Medical Laboratory, Tehran, Iran, for newborn screening programs of IEMs. We incorporated second‐tier tests and secondary biomarkers to improve positive predictive value (PPV).

Results

Statistical data were recorded via call interviewing in 6–8 months after their screening tests. The overall prevalence of IEM was 1:975. The mean age of all participants was 3.9 ± 1.1 days; 5.1% of participants were over 13 days and 7.7% were preterm or underweight. A total of 11384 (29.4%) of the cases were born in a consanguineous family. The type of delivery was the cesarean section in 8332 (51.3%) valid cases. The neonatal screening results had an overall negative predictive value (NPV) of 100% and the overall PPV of 40.2%. The false‐positive rate was 0.15%.

Conclusion

This study showed a high incidence of metabolic disease due to a high rate of consanguineous marriages in Iran and indicated that incorporation of second‐tier tests and secondary biomarkers improves PPV of neonatal screening programs.

Quantitation of non-derivatized free amino acids for detecting inborn errors of metabolism by incorporating mixed-mode chromatography with tandem mass spectrometry

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Analysis of 39 free amino acids in 15 min LC-MS/MS run.

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Validation of method in both plasma and urine.

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Chromatographically resolves leucine, isoleucine, and allo-isoleucine.

Introduction

Amino acids are critical biomarkers for many inborn errors of metabolism, but amino acid analysis is challenging due to the range of chemical properties inherent in these small molecules. Techniques are available for amino acid analysis, but they can suffer from long run times, laborious derivatization, and/or poor resolution of isobaric compounds.

Objective

To develop and validate a method for the quantitation of a non-derivatized free amino acid profile in both plasma and urine samples using mixed-mode chromatography and tandem mass spectrometry.

Methods

Chromatographic conditions were optimized to separate leucine, isoleucine, and allo-isoleucine and maintain analytical runtime at less than 15 min. Sample preparation included a quick protein precipitation followed by LC-MS/MS analysis. Matrix effects, interferences, linearity, carryover, acceptable dilution limits, precision, accuracy, and stability were evaluated in both plasma and urine specimen types.

Results

A total of 38 amino acids and related compounds were successfully quantitated with this method. In addition, argininosuccinic acid was qualitatively analyzed. A full clinical validation was performed that included method comparison to a reference laboratory for plasma and urine with Deming regression slopes ranging from 0.38 to 1.26.

Conclusion

This method represents an alternative to derivatization-based methods, especially in urine samples where interference from metabolites and medications is prevalent.

Newborn Screening in Japan-2021

Japan's Newborn Mass Screening (NBS) was started in 1977 for amino acid metabolism disorders (phenylketonuria (PKU), homocystinuria, maple syrup urine, histidineemia (discontinued in 1993)) and galactosemia at the national level as a national project [...].

Application of the Artificial Intelligence Algorithm Model for Screening of Inborn Errors of Metabolism

Inborn errors of metabolism (IEMs) are strongly related to abnormal growth and development in newborns and can even result in death. In total, 94,648 newborns were enrolled for expanded newborn screening using tandem mass spectrometry (MS/MS) from 2016 to 2020 at the Neonatal Disease Screening Center of the Maternal and Child Health Hospital in Shaoyang City, China. A total of 23 confirmed cases were detected in our study with an incidence rate of 1:4,115. A total of 10 types of IEM were identified, and the most common IEMs were phenylalanine hydroxylase deficiency (PAHD; 1:15,775) and primary carnitine deficiency (PCD; 1:18,930). Mutations in phenylalanine hydroxylase (PAH) and SLC22A5 were the leading causes of IEMs. To evaluate the application effect of artificial intelligence (AI) in newborn screening, we used AI to retrospectively analyze the screening results and found that the false-positive rate could be decreased by more than 24.9% after using AI. Meanwhile, a missed case with neonatal intrahepatic cholestasis citrin deficiency (NICCD) was found, the infant had a normal citrulline level (31 μmol/L; cutoff value of 6-32 μmol/L), indicating that citrulline may not be the best biomarker of intrahepatic cholestasis citrin deficiency. Our results indicated that the use of AI in newborn screening could improve efficiency significantly. Hence, we propose a novel strategy that combines expanded neonatal IEM screening with AI to reduce the occurrence of false positives and false negatives.