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Keywords = Glutaric acidemia type 1

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15 pages, 2286 KiB  
Article
Digital-Tier Strategy Improves Newborn Screening for Glutaric Aciduria Type 1
by Elaine Zaunseder, Julian Teinert, Nikolas Boy, Sven F. Garbade, Saskia Haupt, Patrik Feyh, Georg F. Hoffmann, Stefan Kölker, Ulrike Mütze and Vincent Heuveline
Int. J. Neonatal Screen. 2024, 10(4), 83; https://doi.org/10.3390/ijns10040083 - 21 Dec 2024
Viewed by 1158
Abstract
Glutaric aciduria type 1 (GA1) is a rare inherited metabolic disease increasingly included in newborn screening (NBS) programs worldwide. Because of the broad biochemical spectrum of individuals with GA1 and the lack of reliable second-tier strategies, NBS for GA1 is still confronted with [...] Read more.
Glutaric aciduria type 1 (GA1) is a rare inherited metabolic disease increasingly included in newborn screening (NBS) programs worldwide. Because of the broad biochemical spectrum of individuals with GA1 and the lack of reliable second-tier strategies, NBS for GA1 is still confronted with a high rate of false positives. In this study, we aim to increase the specificity of NBS for GA1 and, hence, to reduce the rate of false positives through machine learning methods. Therefore, we studied NBS profiles from 1,025,953 newborns screened between 2014 and 2023 at the Heidelberg NBS Laboratory, Germany. We identified a significant sex difference, resulting in twice as many false-positives male than female newborns. Moreover, the proposed digital-tier strategy based on logistic regression analysis, ridge regression, and support vector machine reduced the false-positive rate by over 90% compared to regular NBS while identifying all confirmed individuals with GA1 correctly. An in-depth analysis of the profiles revealed that in particular false-positive results with high associated follow-up costs could be reduced significantly. In conclusion, understanding the origin of false-positive NBS and implementing a digital-tier strategy to enhance the specificity of GA1 testing may significantly reduce the burden on newborns and their families from false-positive NBS results. Full article
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10 pages, 380 KiB  
Article
Harnessing Next-Generation Sequencing as a Timely and Accurate Second-Tier Screening Test for Newborn Screening of Inborn Errors of Metabolism
by Toby Chun Hei Chan, Chloe Miu Mak, Matthew Chun Wing Yeung, Eric Chun-Yiu Law, Jana Cheung, Tsz Ki Wong, Vincent Wing-Sang Cheng, Jacky Kwan Ho Lee, Jimmy Chi Lap Wong, Cheuk Wing Fung, Kiran Moti Belaramani, Anne Mei Kwun Kwok and Kwok Yeung Tsang
Int. J. Neonatal Screen. 2024, 10(1), 19; https://doi.org/10.3390/ijns10010019 - 5 Mar 2024
Cited by 2 | Viewed by 2232
Abstract
In this study, we evaluated the implementation of a second-tier genetic screening test using an amplicon-based next-generation sequencing (NGS) panel in our laboratory during the period of 1 September 2021 to 31 August 2022 for the newborn screening (NBS) of six conditions for [...] Read more.
In this study, we evaluated the implementation of a second-tier genetic screening test using an amplicon-based next-generation sequencing (NGS) panel in our laboratory during the period of 1 September 2021 to 31 August 2022 for the newborn screening (NBS) of six conditions for inborn errors of metabolism: citrullinemia type II (MIM #605814), systemic primary carnitine deficiency (MIM #212140), glutaric acidemia type I (MIM #231670), beta-ketothiolase deficiency (#203750), holocarboxylase synthetase deficiency (MIM #253270) and 3-hydroxy-3-methylglutaryl-CoA lyase deficiency (MIM # 246450). The custom-designed NGS panel can detect sequence variants in the relevant genes and also specifically screen for the presence of the hotspot variant IVS16ins3kb of SLC25A13 by the copy number variant calling algorithm. Genetic second-tier tests were performed for 1.8% of a total of 22,883 NBS samples. The false positive rate for these six conditions after the NGS second-tier test was only 0.017%, and two cases of citrullinemia type II would have been missed as false negatives if only biochemical first-tier testing was performed. The confirmed true positive cases were citrullinemia type II (n = 2) and systemic primary carnitine deficiency (n = 1). The false positives were later confirmed to be carrier of citrullinemia type II (n = 2), carrier of glutaric acidemia type I (n = 1) and carrier of systemic primary carnitine deficiency (n = 1). There were no false negatives reported. The incorporation of a second-tier genetic screening test by NGS greatly enhanced our program’s performance with 5-working days turn-around time maintained as before. In addition, early genetic information is available at the time of recall to facilitate better clinical management and genetic counseling. Full article
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20 pages, 1934 KiB  
Article
Glutaryl-CoA Dehydrogenase Misfolding in Glutaric Acidemia Type 1
by Madalena Barroso, Marcus Gertzen, Alexandra F. Puchwein-Schwepcke, Heike Preisler, Andreas Sturm, Dunja D. Reiss, Marta K. Danecka, Ania C. Muntau and Søren W. Gersting
Int. J. Mol. Sci. 2023, 24(17), 13158; https://doi.org/10.3390/ijms241713158 - 24 Aug 2023
Cited by 4 | Viewed by 2858
Abstract
Glutaric acidemia type 1 (GA1) is a neurotoxic metabolic disorder due to glutaryl-CoA dehydrogenase (GCDH) deficiency. The high number of missense variants associated with the disease and their impact on GCDH activity suggest that disturbed protein conformation can affect the biochemical phenotype. We [...] Read more.
Glutaric acidemia type 1 (GA1) is a neurotoxic metabolic disorder due to glutaryl-CoA dehydrogenase (GCDH) deficiency. The high number of missense variants associated with the disease and their impact on GCDH activity suggest that disturbed protein conformation can affect the biochemical phenotype. We aimed to elucidate the molecular basis of protein loss of function in GA1 by performing a parallel analysis in a large panel of GCDH missense variants using different biochemical and biophysical methodologies. Thirteen GCDH variants were investigated in regard to protein stability, hydrophobicity, oligomerization, aggregation, and activity. An altered oligomerization, loss of protein stability and solubility, as well as an augmented susceptibility to aggregation were observed. GA1 variants led to a loss of enzymatic activity, particularly when present at the N-terminal domain. The reduced cellular activity was associated with loss of tetramerization. Our results also suggest a correlation between variant sequence location and cellular protein stability (p < 0.05), with a more pronounced loss of protein observed with variant proximity to the N-terminus. The broad panel of variant-mediated conformational changes of the GCDH protein supports the classification of GA1 as a protein-misfolding disorder. This work supports research toward new therapeutic strategies that target this molecular disease phenotype. Full article
(This article belongs to the Special Issue Protein Folding: 2nd Edition)
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9 pages, 763 KiB  
Article
Evaluation of a Common Internal Standard Material to Reduce Inter-Laboratory Variation and Ensure the Quality, Safety and Efficacy of Expanded Newborn Screening Results When Using Flow Injection Analysis Tandem Mass Spectrometry with Internal Calibration
by Rachel S. Carling, Catharine John, Philippa Goddard, Caroline Griffith, Simon Cowen, Christopher Hopley and Stuart J. Moat
Int. J. Neonatal Screen. 2020, 6(4), 92; https://doi.org/10.3390/ijns6040092 - 19 Nov 2020
Cited by 3 | Viewed by 3338
Abstract
In 2015, the newborn screening (NBS) programmes in England and Wales were expanded to include four additional disorders: Classical Homocystinuria, Isovaleric Acidemia, Glutaric Aciduria Type 1 and Maple Syrup Urine Disease, bringing the total number of analytes quantified to eight: phenylalanine, tyrosine, leucine, [...] Read more.
In 2015, the newborn screening (NBS) programmes in England and Wales were expanded to include four additional disorders: Classical Homocystinuria, Isovaleric Acidemia, Glutaric Aciduria Type 1 and Maple Syrup Urine Disease, bringing the total number of analytes quantified to eight: phenylalanine, tyrosine, leucine, methionine, isovalerylcarnitine, glutarylcarnitine, octanoylcarnitine and decanoylcarnitine. Post-implementation, population data monitoring showed that inter-laboratory variation was greater than expected, with 90th centiles varying from 17% to 59%. We evaluated the effect of stable isotope internal standard (IS) used for quantitation on inter-laboratory variation. Four laboratories analysed routine screening samples (n > 101,820) using a common IS. Inter-laboratory variation was determined for the eight analytes and compared with results obtained using an in-house common IS (n > 102,194). A linear mixed-effects model was fitted to the data. Using a common IS mix reduced the inter-laboratory variation significantly (p < 0.05) for five analytes. For three analytes, the lack of significance was explained by use of individual laboratory “calibration factors”. For screening programmes where laboratories adhere to single analyte cut-off values (COVs), it is important that inter-laboratory variation is minimised, primarily to prevent false positive results. Whilst the use of a common IS helps achieve this, it is evident that instrument set-up also contributes to inter-laboratory variation. Full article
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9 pages, 636 KiB  
Article
Inconsistencies in the Nutrition Management of Glutaric Aciduria Type 1: An International Survey
by Laurie Bernstein, Curtis R. Coughlin, Morgan Drumm, Steven Yannicelli and Fran Rohr
Nutrients 2020, 12(10), 3162; https://doi.org/10.3390/nu12103162 - 16 Oct 2020
Cited by 5 | Viewed by 3715
Abstract
Glutaric aciduria type 1 (GA-1) is a cerebral organic aciduria characterized by striatal injury and progressive movement disorder. Nutrition management shifted from a general restriction of intact protein to targeted restriction of lysine and tryptophan. Recent guidelines advocate for a low-lysine diet using [...] Read more.
Glutaric aciduria type 1 (GA-1) is a cerebral organic aciduria characterized by striatal injury and progressive movement disorder. Nutrition management shifted from a general restriction of intact protein to targeted restriction of lysine and tryptophan. Recent guidelines advocate for a low-lysine diet using lysine-free, tryptophan-reduced medical foods. GA-1 guideline recommendations for dietary management of patients over the age of six are unclear, ranging from avoiding excessive intake of intact protein to counting milligrams of lysine intake. A 22–question survey on the nutrition management of GA-1 was developed with the goal of understanding approaches to diet management for patients identified by newborn screening under age six years compared to management after diet liberalization, as well as to gain insight into how clinicians define diet liberalization. Seventy-six responses (25% of possible responses) to the survey were received. Nutrition management with GA-1 is divergent among surveyed clinicians. There was congruency among survey responses to the guidelines, but there is still uncertainty about how to counsel patients on diet optimization and when diet liberalization should occur. Ongoing clinical research and better understanding of the natural history of this disease will help establish stronger recommendations from which clinicians can best counsel families. Full article
(This article belongs to the Section Clinical Nutrition)
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12 pages, 1534 KiB  
Article
Reducing False-Positive Results in Newborn Screening Using Machine Learning
by Gang Peng, Yishuo Tang, Tina M. Cowan, Gregory M. Enns, Hongyu Zhao and Curt Scharfe
Int. J. Neonatal Screen. 2020, 6(1), 16; https://doi.org/10.3390/ijns6010016 - 3 Mar 2020
Cited by 54 | Viewed by 7177
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue CLIR Applications for Newborn Screening)
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