ArticleGenome biology2023
Predicting disease severity in metachromatic leukodystrophy using protein activity and a patient phenotype matrix.
Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Consensus guidelines for the monitoring and management of metachromatic leukodystrophy in the United States.Cytotherapy · 2024Guideline
- Clinical management of metachromatic leukodystrophy cases identified in the German and Austrian Newborn screening pilots.Orphanet journal of rare diseases · 2026Article
- Preliminary Data of the First Year of Newborn Screening for Metachromatic Leukodystrophy (MLD) in Lombardy.International journal of neonatal screening · 2026Article
- Benchmarking genetic birth prevalence estimates against newborn screening data.American journal of human genetics · 2026Article
- Gallbladder mucinous carcinoma in a child with metachromatic leukodystrophy, case report and literature review.BMC pediatrics · 2026Review
- In Vitro Screening of an FDA-Approved Chemical Library for Arylsulfatase A Using Fibroblast Cells Derived From Patients With MLD.BioMed research international · 2026Article
- Newborn Screening for Metachromatic Leukodystrophy: A Systematic Literature Review.International journal of neonatal screening · 2025Review
- Assessment the Efficacy of the CRISPR System for Inducing Mutations in the AIMP2 Gene to Create a Cell Line Model of HLD17 Disease.Molecular biotechnology · 2025Article
- ARSA Variants Associated With Cognitive Decline and Long-Term Preservation of Motor Function in Metachromatic Leukodystrophy.Journal of inherited metabolic disease · 2025Observational
- Metachromatic Leukodystrophy: New Therapy Advancements and Emerging Research Directions.Neurology · 2025Review
- Screening for Life: Perspectives From Adult Metabolic Specialists on Newborn Screening for Inherited Metabolic Diseases.Journal of inherited metabolic disease · 2025Review
- QAFI: a novel method for quantitative estimation of missense variant impact using protein-specific predictors and ensemble learning.Human genetics · 2025Article
- Evaluation of enzyme activity predictions for variants of unknown significance in Arylsulfatase A.Human genetics · 2025Article
- Characterization of gallbladder disease in metachromatic leukodystrophy across the lifespan.Molecular genetics and metabolism · 2025Article
- Evaluation of enzyme activity predictions for variants of unknown significance in Arylsulfatase A.bioRxiv : the preprint server for biology · 2024Article
- Inventory of current practices regarding hematopoietic stem cell transplantation in metachromatic leukodystrophy in Europe and neighboring countries.Orphanet journal of rare diseases · 2024Article
- First-Tier Next Generation Sequencing for Newborn Screening: An Important Role for Biochemical Second-Tier Testing.Genetics in medicine open · 2023Article
Corrections and comments
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Authors and funding
12 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundMetachromatic leukodystrophy (MLD) is a lysosomal storage disorder caused by mutations in the arylsulfatase A gene (ARSA) and categorized into three subtypes according to age of onset. The functional effect of most ARSA mutants remains unknown; better understanding of the genotype-phenotype relationship is required to support newborn screening (NBS) and guide treatment.
resultsWe collected a patient data set from the literature that relates disease severity to ARSA genotype in 489 individuals with MLD. Patient-based data were used to develop a phenotype matrix that predicts MLD phenotype given ARSA alleles in a patient's genotype with 76% accuracy. We then employed a high-throughput enzyme activity assay using mass spectrometry to explore the function of ARSA variants from the curated patient data set and the Genome Aggregation Database (gnomAD). We observed evidence that 36% of variants of unknown significance (VUS) in ARSA may be pathogenic. By classifying functional effects for 251 VUS from gnomAD, we reduced the incidence of genotypes of unknown significance (GUS) by over 98.5% in the overall population.
conclusionsThese results provide an additional tool for clinicians to anticipate the disease course in MLD patients, identifying individuals at high risk of severe disease to support treatment access. Our results suggest that more than 1 in 3 VUS in ARSA may be pathogenic. We show that combining genetic and biochemical information increases diagnostic yield. Our strategy may apply to other recessive diseases, providing a tool to address the challenge of interpreting VUS within genotype-phenotype relationships and NBS.
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