The mucopolysaccharidoses (MPSs) include 11 different conditions caused by specific enzyme deficiencies in the degradation pathway of glycosaminoglycans (GAGs). Although most MPS types present increased levels of GAGs in tissues, including blood and urine, diagnosis is challenging as specific enzyme assays are needed for the correct diagnosis. Enzyme assays are usually performed in blood, with some samples (as leukocytes) providing a final diagnosis, while others (such as dried blood spots) still being considered as screening methods. The identification of variants in the specific genes that encode each MPS-related enzyme is helpful for diagnosis confirmation (when needed), carrier detection, genetic counseling, prenatal diagnosis (preferably in combination with enzyme assays) and phenotype prediction. Although the usual diagnostic flow in high-risk patients starts with the measurement of urinary GAGs, it continues with specific enzyme assays and is completed with mutation identification; there is a growing trend to have genotype-based investigations performed at the beginning of the investigation. In such cases, confirmation of pathogenicity of the variants identified should be confirmed by measurement of enzyme activity and/or identification and/or quantification of GAG species. As there is a growing number of countries performing newborn screening for MPS diseases, the investigation of a low enzyme activity by the measurement of GAG species concentration and identification of gene mutations in the same DBS sample is recommended before the suspicion of MPS is taken to the family. With specific therapies already available for most MPS patients, and with clinical trials in progress for many conditions, the specific diagnosis of MPS as early as possible is becoming increasingly necessary. In this review, we describe traditional and the most up to date diagnostic methods for mucopolysaccharidoses.

Precision medicine (PM) is an emerging approach for disease treatment and prevention that accounts for the individual variability in the genes, environment, and lifestyle of each person. Lysosomal diseases (LDs) are a group of genetic metabolic disorders that include approximately 70 monogenic conditions caused by a defect in lysosomal function. LDs may result from primary lysosomal enzyme deficiencies or impairments in membrane-associated proteins, lysosomal enzyme activators, or modifiers that affect lysosomal function. LDs are heterogeneous disorders, and the phenotype of the affected individual depends on the type of substrate and where it accumulates, which may be impacted by the type of genetic change and residual enzymatic activity. LDs are individually rare, with a combined incidence of approximately 1:4000 individuals. Specific therapies are already available for several LDs, and many more are in development. Early identification may enable disease course prediction and a specific intervention, which is very important for clinical outcome. Driven by advances in omics technology, PM aims to provide the most appropriate management for each patient based on the disease susceptibility or treatment response predictions for specific subgroups. In this review, we focused on the emerging diagnostic technologies that may help to optimize the management of each LD patient and the therapeutic options available, as well as in clinical developments that enable customized approaches to be selected for each subject, according to the principles of PM.

Filocamo et al. recently published a paper describing the presence of a pseudodeficiency allele, constituted by p.Ser141Ser and p.Arg737Gly polymorphisms at the NAGLU gene, which leads to a reduced level of the alpha-N-acetyl-D-glucosaminidase activity. Based on analysis performed in Brazilian patients, using a customized gene panel containing SGSH, NAGLU, HGSNAT and GNS we observed that p.Ser141Ser (rs659497) and p.Arg737Gly (rs86312) variants were present in homozygosis in all of our MPS IIIB patients and in the majority of MPS IIIA, IIIC and IIID patients, and there was no significant decrease of the alpha-N-acetyl-D-glucosaminidase enzyme activity in this group when compared with those without the “pseudodeficiency allele”. Thus, we suggest that these two variants are not producing a pseudodeficiency allele.

Preterm birth (PTB) is the main condition related to perinatal morbimortality worldwide. The aim of this study was to identify gene-environment interactions associated with spontaneous PTB or its predictors. We carried out a retrospective case-control study including parental sociodemographic and obstetric data as well as newborn genetic variants of 69 preterm and 61 at term newborns born at a maternity hospital from Tucumán, Argentina, between 2005 and 2010. A data-driven Bayesian network including the main PTB predictors was created where we identified gene-environment interactions. We used logistic regressions to calculate the odds ratios and confidence intervals of the interactions. From the main PTB predictors (nine exposures and six genetic variants) we identified an interaction between low neighbourhood socioeconomic status and rs2074351 (PON1, genotype GG) variant that was associated with an increased risk of toxoplasmosis (odds ratio 12.51, confidence interval 95%: 1.71 - 91.36). The results of this exploratory study suggest that structural social disparities could influence the PTB risk by increasing the frequency of exposures that potentiate the risk associated with individual characteristics such as genetic traits. Future studies with larger sample sizes are necessary to confirm these findings.