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.

Improved diagnosis of citrin deficiency by newborn screening using a molecular second-tier test.

BACKGROUND: Citrin deficiency is an autosomal recessive disorder caused by variants of the SLC25A13 gene. Although newborn screening (NBS) provides an opportunity for its early diagnosis and treatment, citrin deficiency detection rates remain lower than those estimated. METHODS: Before 2018, NBS for citrin deficiency was based on citrulline levels alone. In June 2018, a second-tier molecular test was implemented to detect 11 common variants of the SLC25A13 gene and improve the NBS detection rates. This study compares the incidence rates and costs before and after the second-tier implementation. RESULTS: Prior to 2018, five subjects were diagnosed via NBS, and 12 of 555,449 newborns screened were missed. In comparison, 11 subjects were diagnosed out of 198,071 newborns screened after 2018, and there were no false-negatives. The citrin deficiency detection rate increased from 1/32,673 to 1/18,006 after the second-tier test was implemented, with only a minimal increase in the total cost. The number of false-positive in our cohort was tolerable. Subjects with citrin deficiency may present with borderline elevated citrulline levels; these can remain slightly elevated or increase considerably on retest. Four patients (80%) detected prior to second-tier testing and six patients (55%) detected after it was implemented were identified based on the citrulline levels alone. However, at the time of second blood sampling, the normal citrulline level of five subjects did not exclude a citrin deficiency diagnosis. CONCLUSIONS: Our study shows that it is vital and cost-effective to employ second-tier molecular testing to improve the detection of citrin deficiency by NBS.

21-Deoxycortisol is a Key Screening Marker for 21-Hydroxylase Deficiency.

OBJECTIVES: To assess whether 21-deoxycortisol (21deoxy) can be used to predict 21-hydroxylase deficiency (21OHD) in newborns and to evaluate the influence of gestational age and the timing of collection on 21deoxy concentrations. STUDY DESIGN: 17-hydroxyprogesterone (17OHP) and 21deoxy levels were measured in 906 newborn screening specimens (851 unaffected newborns, 55 confirmed cases of 21OHD) to compare their ability to identify babies with 21OHD. In addition, these 2 steroids were assessed in the unaffected cohort to determine the influence of gestational age (ranging from 23 to 42 weeks) and the timing of specimen collection on the measured concentrations. RESULTS: The gestational age of the newborn impacted both 17OHP and 21deoxy concentrations, but the degree of influence was more substantial for 17OHP. Timing of collection did not affect 21deoxy concentration. Moreover, 21deoxy was a better predictor of 21OHD status compared with 17OHP, with little overlap in concentrations between the unaffected population and confirmed cases of 21OHD. A streamlined decision tree using solely 21deoxy (cutoff value, 0.85 ng/mL) yielded a 91.7% positive predictive value for 21OHD screening. CONCLUSIONS: Our findings demonstrate that 21deoxy is a key disease marker of 21OHD and can be used to improve the accuracy of newborn screening for this disorder.

Portuguese Neonatal Screening Program: A Cohort Study of 18 Years Using MS/MS.

The Portuguese Neonatal Screening Program (PNSP) conducts nationwide screening for rare diseases, covering nearly 100% of neonates and screening for 28 disorders, including 24 inborn errors of metabolism (IEMs). The study's purpose is to assess the epidemiology of the screened metabolic diseases and to evaluate the impact of second-tier testing (2TT) within the PNSP. From 2004 to 2022, 1,764,830 neonates underwent screening using tandem mass spectrometry (MS/MS) to analyze amino acids and acylcarnitines in dried blood spot samples. 2TT was applied when necessary. Neonates with profiles indicating an IEM were reported to a reference treatment center, and subsequent biochemical and molecular studies were conducted for diagnostic confirmation. Among the screened neonates, 677 patients of IEM were identified, yielding an estimated birth prevalence of 1:2607 neonates. The introduction of 2TT significantly reduced false positives for various disorders, and 59 maternal cases were also detected. This study underscores the transformative role of MS/MS in neonatal screening, emphasizing the positive impact of 2TT in enhancing sensitivity, specificity, and positive predictive value. Our data highlight the efficiency and robustness of neonatal screening for IEM in Portugal, contributing to early and life-changing diagnoses.

dbRUSP: An Interactive Database to Investigate Inborn Metabolic Differences for Improved Genetic Disease Screening.

The Recommended Uniform Screening Panel (RUSP) contains more than forty metabolic disorders recommended for inclusion in universal newborn screening (NBS). Tandem-mass-spectrometry-based screening of metabolic analytes in dried blood spot samples identifies most affected newborns, along with a number of false positive results. Due to their influence on blood metabolite levels, continuous and categorical covariates such as gestational age, birth weight, age at blood collection, sex, parent-reported ethnicity, and parenteral nutrition status have been shown to reduce the accuracy of screening. Here, we developed a database and web-based tools (dbRUSP) for the analysis of 41 NBS metabolites and six variables for a cohort of 500,539 screen-negative newborns reported by the California NBS program. The interactive database, built using the R shiny package, contains separate modules to study the influence of single variables and joint effects of multiple variables on metabolite levels. Users can input an individual's variables to obtain metabolite level reference ranges and utilize dbRUSP to select new candidate markers for the detection of metabolic conditions. The open-source format facilitates the development of data mining algorithms that incorporate the influence of covariates on metabolism to increase accuracy in genetic disease screening.

Screening for Methylmalonic and Propionic Acidemia: Clinical Outcomes and Follow-Up Recommendations.

Wisconsin's newborn screening program implemented second-tier testing on specimens with elevated propionylcarnitine (C3) to aid in the identification of newborns with propionic and methylmalonic acidemias. The differential diagnosis for elevated C3 also includes acquired vitamin B12 deficiency, which is currently categorized as a false positive screen. The goal of this study was to summarize screening data and evaluate their effectiveness at establishing diagnoses and categorizing false positive cases. All Wisconsin newborns born between 2013 and 2019 with a positive first-tier screen for C3 were included in this study. For each case the first- and second-tier newborn screening data and confirmatory test results were compiled. The clinical determination for each case was reviewed and categorized into groups: inborn error of metabolism, maternal B12 deficiency, infant B12 deficiency, and false positive. A review of the screening data showed a significant overlap in the concentration of biomarkers for newborns with genetic versus acquired disease. Additionally, a review of confirmatory test results showed incomplete ascertainment of maternal vitamin B12 status. The Wisconsin newborn screening program recommended a confirmatory testing algorithm to aid in the diagnosis of inborn errors of metabolism and acquired vitamin B12 deficiency.

Incorporation of Second-Tier Biomarker Testing Improves the Specificity of Newborn Screening for Mucopolysaccharidosis Type I.

Enzyme-based newborn screening for Mucopolysaccharidosis type I (MPS I) has a high false-positive rate due to the prevalence of pseudodeficiency alleles, often resulting in unnecessary and costly follow up. The glycosaminoglycans (GAGs), dermatan sulfate (DS) and heparan sulfate (HS) are both substrates for α-l-iduronidase (IDUA). These GAGs are elevated in patients with MPS I and have been shown to be promising biomarkers for both primary and second-tier testing. Since February 2016, we have measured DS and HS in 1213 specimens submitted on infants at risk for MPS I based on newborn screening. Molecular correlation was available for 157 of the tested cases. Samples from infants with MPS I confirmed by IDUA molecular analysis all had significantly elevated levels of DS and HS compared to those with confirmed pseudodeficiency and/or heterozygosity. Analysis of our testing population and correlation with molecular results identified few discrepant outcomes and uncovered no evidence of false-negative cases. We have demonstrated that blood spot GAGs analysis accurately discriminates between patients with confirmed MPS I and false-positive cases due to pseudodeficiency or heterozygosity and increases the specificity of newborn screening for MPS I.

Reducing False-Positive Results in Newborn Screening Using Machine Learning.

Newborn screening (NBS) for inborn metabolic disorders is a highly successful public health program that by design is accompanied by false-positive results. Here we trained a Random Forest machine learning classifier on screening data to improve prediction of true and false positives. Data included 39 metabolic analytes detected by tandem mass spectrometry and clinical variables such as gestational age and birth weight. Analytical performance was evaluated for a cohort of 2777 screen positives reported by the California NBS program, which consisted of 235 confirmed cases and 2542 false positives for one of four disorders: glutaric acidemia type 1 (GA-1), methylmalonic acidemia (MMA), ornithine transcarbamylase deficiency (OTCD), and very long-chain acyl-CoA dehydrogenase deficiency (VLCADD). Without changing the sensitivity to detect these disorders in screening, Random Forest-based analysis of all metabolites reduced the number of false positives for GA-1 by 89%, for MMA by 45%, for OTCD by 98%, and for VLCADD by 2%. All primary disease markers and previously reported analytes such as methionine for MMA and OTCD were among the top-ranked analytes. Random Forest's ability to classify GA-1 false positives was found similar to results obtained using Clinical Laboratory Integrated Reports (CLIR). We developed an online Random Forest tool for interpretive analysis of increasingly complex data from newborn screening.

Application of Principal Component Analysis to Newborn Screening for Congenital Adrenal Hyperplasia.

PURPOSE: Newborn screening laboratories are challenged to develop reporting algorithms that accurately identify babies at increased risk for congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency (21OHD). Screening algorithms typically use cutoff values for a key steroid(s) and include considerations for covariates, such as gestational age or birth weight, but false-positive and false-negative results are still too frequent, preventing accurate assessments. Principal component analysis (PCA) is a statistical method that reduces high-dimensional data to a small number of components, capturing patterns of association that may be relevant to the outcome of interest. To our knowledge, PCA has not been evaluated in the newborn screening setting to determine whether it can improve the positive predictive value of 21OHD screening. METHODS: PCA was applied to a data set of 920 newborns with measured concentrations of 5 key steroids that are known to be perturbed in patients with 21OHD. A decision tree for the known outcomes (confirmed 21OHD cases and unaffected individuals) was created with 2 principal components as predictors. The effectiveness of the PCA-derived decision tree was compared with the current algorithm. RESULTS: PCA improved the positive predictive value of 21OHD screening from 20.0% to 66.7% in a retrospective study comparing the current algorithm to a tree-based algorithm using PCA-derived variables. The streamlined PCA-derived decision tree, comprising only 3 assessment points, greatly simplified the 21OHD reporting algorithm. CONCLUSIONS: This first report of PCA applied to newborn screening for 21OHD demonstrates enhanced detection of affected individuals within the unaffected population.

Genomic Analysis of Historical Cases with Positive Newborn Screens for Short-Chain Acyl-CoA Dehydrogenase Deficiency Shows That a Validated Second-Tier Biochemical Test Can Replace Future Sequencing.

Short-chain acyl-CoA dehydrogenase deficiency (SCADD) is a rare autosomal recessive disorder of ß-oxidation caused by pathogenic variants in the ACADS gene. Analyte testing for SCADD in blood and urine, including newborn screening (NBS) using tandem mass spectrometry (MS/MS) on dried blood spots (DBSs), is complicated by the presence of two relatively common ACADS variants (c.625G>A and c.511C>T). Individuals homozygous for these variants or compound heterozygous do not have clinical disease but do have reduced short-chain acyl-CoA dehydrogenase (SCAD) activity, resulting in elevated blood and urine metabolites. As part of a larger study of the potential role of exome sequencing in NBS in California, we reviewed ACADS sequence and MS/MS data from DBSs from a cohort of 74 patients identified to have SCADD. Of this cohort, approximately 60% had one or more of the common variants and did not have the two rare variants, and thus would need no further testing. Retrospective analysis of ethylmalonic acid, glutaric acid, 2-hydroxyglutaric acid, 3-hydroxyglutaric acid, and methylsuccinic acid demonstrated that second-tier testing applied before the release of the newborn screening result could reduce referrals by over 50% and improve the positive predictive value for SCADD to above 75%.

Wisconsin's Screening Algorithm for the Identification of Newborns with Congenital Adrenal Hyperplasia.

Newborn screening for congenital adrenal hyperplasia (CAH) has one of the highest false positive rates of any of the diseases on the Wisconsin panel. This is largely due to the first-tier immune assay cross-reactivity and physiological changes in the concentration of 17-hydroxyprogesterone during the first few days of life. To improve screening for CAH, Wisconsin developed a second-tier assay to quantify four different steroids (17-hydroxyprogesterone, 21-deoxycortisol, androstenedione, and cortisol) by liquid chromatography-tandem mass spectrometry (LC-MSMS) in dried blood spots. From validation studies which included the testing of confirmed CAH patients, Wisconsin established its own reporting algorithm that incorporates steroid concentrations as well as two different ratios-the birth weight and the collection time-to identify babies at risk for CAH. Using the newly developed method and algorithm, the false positive rate for the CAH screening was reduced by 95%. Patients with both classical forms of CAH, salt-wasting and simple virilizing, were identified. This study replicates and expands upon previous work to develop a second-tier LC-MSMS steroid profiling screening assay for CAH. The validation and prospective study results provide evidence for an extensive reporting algorithm that incorporates multiple steroids, birth weight, and collection times.

Newborn screening for dihydrolipoamide dehydrogenase deficiency: Citrulline as a useful analyte.

Dihydrolipoamide dehydrogenase deficiency, also known as maple syrup urine disease (MSUD) type III, is caused by the deficiency of the E3 subunit of branched chain alpha-ketoacid dehydrogenase (BCKDH), α-ketoglutarate dehydrogenase (αKGDH), and pyruvate dehydrogenase (PDH). DLD deficiency variably presents with either a severe neonatal encephalopathic phenotype or a primarily hepatic phenotype. As a variant form of MSUD, it is considered a core condition recommended for newborn screening. The detection of variant MSUD forms has proven difficult in the past with no asymptomatic DLD deficiency patients identified by current newborn screening strategies. Citrulline has recently been identified as an elevated dried blood spot (DBS) metabolite in symptomatic patients affected with DLD deficiency. Here we report the retrospective DBS analysis and second-tier allo-isoleucine testing of 2 DLD deficiency patients. We show that an elevated citrulline and an elevated allo-isoleucine on second-tier testing can be used to successfully detect DLD deficiency. We additionally recommend that DLD deficiency be included in the "citrullinemia/elevated citrulline" ACMG Act Sheet and Algorithm.