Prevalence rates of mucopolysaccharidoses in Poland.
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ABSTRACT:
SUBMITTER: Jurecka A
PROVIDER: S-EPMC4412687 | biostudies-literature | 2015 May
REPOSITORIES: biostudies-literature
Publications
Prevalence rates of mucopolysaccharidoses in Poland.
Jurecka Agnieszka A Ługowska Agnieszka A Golda Adam A Czartoryska Barbara B Tylki-Szymańska Anna A
Journal of applied genetics 20141204 2
The aim of this study was to determine the prevalence rates of mucopolysaccharidoses in Poland and to compare them with other European countries. A retrospective epidemiological survey covering the period between 1970 and 2010 was implemented. Multiple ascertainment sources were used to identify affected patients. The overall prevalence of mucopolysaccharidoses in the Polish population was 1.81 per 100,000. Five different mucopolysaccharidoses were diagnosed in a total of 392 individuals. MPS II ...[more]
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Project description:Previous studies on the prevalence of mucopolysaccharidoses (MPS) in different populations have shown considerable variations. There are, however, few data with regard to the prevalence of MPSs in Fenno-Ugric populations or in north-eastern Europe, except for a report about Scandinavian countries. A retrospective epidemiological study of MPSs in Estonia was undertaken, and live-birth prevalence of MPS patients born between 1985 and 2006 was estimated. The live-birth prevalence for all MPS subtypes was found to be 4.05 per 100,000 live births, which is consistent with most other European studies. MPS II had the highest calculated incidence, with 2.16 per 100,000 live births (4.2 per 100,000 male live births), forming 53% of all diagnosed MPS cases, and was twice as high as in other studied European populations. The second most common subtype was MPS IIIA, with a live-birth prevalence of 1.62 in 100,000 live births. With 0.27 out of 100,000 live births, MPS VI had the third-highest live-birth prevalence. No cases of MPS I were diagnosed in Estonia, making the prevalence of MPS I in Estonia much lower than in other European populations. MPSs are the third most frequent inborn error of metabolism in Estonia after phenylketonuria and galactosemia.
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Project description:BackgroundIn this study, the prevalence of different types of mucopolysaccharidoses (MPS) was estimated based on data from the exome aggregation consortium (ExAC) and the genome aggregation database (gnomAD). The population-based allele frequencies were used to identify potential disease-causing variants on each gene related to MPS I to IX (except MPS II).MethodsWe evaluated the canonical transcripts and excluded homozygous, intronic, 3', and 5' UTR variants. Frameshift and in-frame insertions and deletions were evaluated using the SIFT Indel tool. Splice variants were evaluated using SpliceAI and Human Splice Finder 3.0 (HSF). Loss-of-function single nucleotide variants in coding regions were classified as potentially pathogenic, while synonymous variants outside the exon-intron boundaries were deemed non-pathogenic. Missense variants were evaluated by five in silico prediction tools, and only those predicted to be damaging by at least three different algorithms were considered disease-causing.ResultsThe combined frequencies of selected variants (ranged from 127 in GNS to 259 in IDUA) were used to calculate prevalence based on Hardy-Weinberg's equilibrium. The maximum estimated prevalence ranged from 0.46 per 100,000 for MPSIIID to 7.1 per 100,000 for MPS I. Overall, the estimated prevalence of all types of MPS was higher than what has been published in the literature. This difference may be due to misdiagnoses and/or underdiagnoses, especially of the attenuated forms of MPS. However, overestimation of the number of disease-causing variants by in silico predictors cannot be ruled out. Even so, the disease prevalences are similar to those reported in diagnosis-based prevalence studies.ConclusionWe report on an approach to estimate the prevalence of different types of MPS based on publicly available population-based genomic data, which may help health systems to be better prepared to deal with these conditions and provide support to initiatives on diagnosis and management of MPS.
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Project description:Mucopolysaccharidoses (MPS) are a group of lysosomal storage disorders (LSDs) caused by a deficiency of lysosomal enzymes, leading to a wide range of various clinical symptoms depending upon the type of MPS or its severity. Enzyme replacement therapy (ERT), hematopoietic stem cell transplantation (HSCT), substrate reduction therapy (SRT), and various surgical procedures are currently available for patients with MPS. However, there is no curative treatment for this group of disorders. Gene therapy should be a one-time permanent therapy, repairing the cause of enzyme deficiency. Preclinical studies of gene therapy for MPS have been developed over the past three decades. Currently, clinical trials of gene therapy for some types of MPS are ongoing in the United States, some European countries, and Australia. Here, in this review, we summarize the development of gene therapy for MPS in preclinical and clinical trials.
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Project description:Genome editing holds the promise of one-off and potentially curative therapies for many patients with genetic diseases. This is especially true for patients affected by mucopolysaccharidoses as the disease pathophysiology is amenable to correction using multiple approaches. Ex vivo and in vivo genome editing platforms have been tested primarily on MSPI and MPSII, with in vivo approaches having reached clinical testing in both diseases. Though we still await proof of efficacy in humans, the therapeutic tools established for these two diseases should pave the way for other mucopolysaccharidoses. Herein, we review the current preclinical and clinical development studies, using genome editing as a therapeutic approach for these diseases. The development of new genome editing platforms and the variety of genetic modifications possible with each tool provide potential applications of genome editing for mucopolysaccharidoses, which vastly exceed the potential of current approaches. We expect that in a not-so-distant future, more genome editing-based strategies will be established, and individual diseases will be treated through multiple approaches.
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