An algorithm to predict phenotypic severity in mucopolysaccharidosis type I in the first month of life
Insights
This study developed an algorithm using genetic, biochemical, and clinical data to predict Mucopolysaccharidosis type I (MPS I) phenotypes. This aids in early, optimal treatment for MPS I patients.
Area of Science:
- Biochemistry
- Genetics
- Pediatrics
Background:
- Mucopolysaccharidosis type I (MPS I) is a genetic disorder impacting multiple organs due to alpha-L-iduronidase (IDUA) deficiency.
- Disease severity varies, with Hurler phenotype (MPS I-H) causing cognitive impairment, necessitating hematopoietic stem cell transplantation.
- Milder MPS I phenotypes benefit from enzyme replacement therapy, highlighting the need for accurate diagnosis.
Purpose of the Study:
- To develop a predictive algorithm for MPS I phenotypes using readily available data.
- To enable timely and appropriate treatment initiation for MPS I patients, especially following newborn screening (NBS).
Main Methods:
- Collected genotypic and phenotypic data from 30 MPS I patients.
- Measured IDUA enzyme activity in fibroblast cultures for 18 patients.
- Gathered clinical characteristics from the first month of life for 23 patients.
Main Results:
- Specific mutations accurately identified MPS I-H patients (100% specificity, 82% sensitivity).
- Fibroblast IDUA activity levels (<0.32 nmol x mg(-1) x hr(-1) for MPS I-H, >0.66 for attenuated) aided classification.
- A combined genetic, biochemical, and clinical model achieved 100% sensitivity and specificity in this cohort.
Conclusions:
- An algorithm integrating genetic, biochemical, and clinical data can predict MPS I phenotype.
- This predictive model is valuable for newborns, facilitating prompt and optimal treatment strategies.
- Early prediction is crucial for managing MPS I and improving patient outcomes.
Introduction:
Mucopolysaccharidosis type I (MPS I) is a progressive multisystem lysosomal storage disease caused by deficiency of the enzyme α-L-iduronidase (IDUA). Patients present with a continuous spectrum of disease severity, and the most severely affected patients (Hurler phenotype; MPS I-H) develop progressive cognitive impairment. The treatment of choice for MPS I-H patients is haematopoietic stem cell transplantation, while patients with the more attenuated phenotypes benefit from enzyme replacement therapy.
Methods:
Thirty patients were included in this study. Genotypes were collected from all patients and all patients were phenotypically categorized at an age of > 18 months based on the clinical course of the disease. In 18 patients, IDUA activity in fibroblast cultures was measured using an optimized IDUA assay. Clinical characteristics from the first month of life were collected from 23 patients.
Results:
Homozygosity or compound heterozygosity for specific mutations which are associated with MPS I-H, discriminated a subset of patients with MPS I-H from patients with more attenuated phenotypes (specificity 100%, sensitivity 82%). Next, we found that enzymatic analysis of IDUA activity in fibroblasts allowed identification of patients affected by MPS I-H. Therefore, residual IDUA activity in fibroblasts was introduced as second step in the algorithm. Patients with an IDUA activity of < 0.32 nmol x mg(-1) × hr(-1) invariably were MPS I-H patients, while an IDUA activity of > 0.66 nmol × mg(-1) × hr(-1) was only observed in more attenuated patients. Patients with an intermediate IDUA activity could be further classified by the presence of differentiating clinical characteristics, resulting in a model with 100% sensitivity and specificity for this cohort of patients.
Conclusion:
Using genetic, biochemical and clinical characteristics, all potentially available in the newborn period, an algorithm was developed to predict the MPS I phenotype, allowing timely initiation of the optimal treatment strategy after introduction of NBS.
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