Analysis of Mucopolysaccharidosis Type VI through Integrative Functional Metabolomics

Application of tandem mass spectrometry in the screening and diagnosis of mucopolysaccharidoses

Mucopolysaccharidoses (MPSs) are caused by a deficiency in the enzymes needed to degrade glycosaminoglycans (GAGs) in the lysosome. The storage of GAGs leads to the involvement of several systems and even to the death of the patient. In recent years, an increasing number of therapies have increased the treatment options available to patients. Early treatment is beneficial in improving the prognosis, but children with MPSs are often delayed in their diagnosis. Therefore, there is an urgent need to develop a method for early screening and diagnosis of the disease. Tandem mass spectrometry (MS/MS) is an analytical method that can detect multiple substrates or enzymes simultaneously. GAGs are reliable markers of MPSs. MS/MS can be used to screen children at an early stage of the disease, to improve prognosis by treating them before symptoms appear, to evaluate the effectiveness of treatment, and for metabolomic analysis or to find suitable biomarkers. In the future, MS/MS could be used to further identify suitable biomarkers for MPSs for early diagnosis and to detect efficacy.

An evaluation of untargeted metabolomics methods to characterize inborn errors of metabolism

Inborn errors of metabolism (IEMs) encompass a diverse group of disorders that can be difficult to classify due to heterogenous clinical, molecular, and biochemical manifestations. Untargeted metabolomics platforms have become a popular approach to analyze IEM patient samples because of their ability to detect many metabolites at once, accelerating discovery of novel biomarkers, and metabolic mechanisms of disease. However, there are concerns about the reproducibility of untargeted metabolomics research due to the absence of uniform reporting practices, data analyses, and experimental design guidelines. Therefore, we critically evaluated published untargeted metabolomic platforms used to characterize IEMs to summarize the strengths and areas for improvement of this technology as it progresses towards the clinical laboratory. A total of 96 distinct IEMs were collectively evaluated by the included studies. However, most of these IEMs were evaluated by a single untargeted metabolomic method, in a single study, with a limited cohort size (55/96, 57%). The goals of the included studies generally fell into two, often overlapping, categories: detecting known biomarkers from many biochemically distinct IEMs using a single platform, and detecting novel metabolites or metabolic pathways. There was notable diversity in the design of the untargeted metabolomic platforms. Importantly, the majority of studies reported adherence to quality metrics, including the use of quality control samples and internal standards in their experiments, as well as confirmation of at least some of their feature annotations with commercial reference standards. Future applications of untargeted metabolomics platforms to the study of IEMs should move beyond single-subject analyses, and evaluate reproducibility using a prospective, or validation cohort.

Untargeted Metabolomic Analysis of Sjögren-Larsson Syndrome Reveals a Distinctive Pattern of Multiple Disrupted Biochemical Pathways

Sjögren-Larsson syndrome (SLS) is a rare inherited neurocutaneous disease characterized by ichthyosis, spastic diplegia or tetraplegia, intellectual disability and a distinctive retinopathy. SLS is caused by bi-allelic mutations in ALDH3A2, which codes for fatty aldehyde dehydrogenase (FALDH) and results in abnormal lipid metabolism. The biochemical abnormalities in SLS are not completely known, and the pathogenic mechanisms leading to symptoms are still unclear. To search for pathways that are perturbed in SLS, we performed untargeted metabolomic screening in 20 SLS subjects along with age- and sex-matched controls. Of 823 identified metabolites in plasma, 121 (14.7%) quantitatively differed in the overall SLS cohort from controls; 77 metabolites were decreased and 44 increased. Pathway analysis pointed to disrupted metabolism of sphingolipids, sterols, bile acids, glycogen, purines and certain amino acids such as tryptophan, aspartate and phenylalanine. Random forest analysis identified a unique metabolomic profile that had a predictive accuracy of 100% for discriminating SLS from controls. These results provide new insight into the abnormal biochemical pathways that likely contribute to disease in SLS and may constitute a biomarker panel for diagnosis and future therapeutic studies.

Untargeted LC-HRMS metabolomics reveals candidate biomarkers for mucopolysaccharidoses

BACKGROUND

Mucopolysaccharidoses (MPSs) are inherited genetic diseases caused by an absence or deficiency of lysosomal enzymes responsible for catabolizing glycosaminoglycans (GAGs). Undiagnosed patients, or those without adequate treatment in early life, can be severely and irreversibly affected by the disease. In this study, we applied liquid chromatography-high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics to identify potential biomarkers for MPS disorders to better understand how MPS may affect the metabolome of patients.

METHODS

Urine samples from 37 MPS patients (types I, II, III, IV, and VI; untreated and treated with enzyme replacement therapy (ERT)) and 38 controls were analyzed by LC-HRMS. Data were processed by an untargeted metabolomics workflow and submitted to multivariate statistical analyses to reveal significant differences between the MPS and control groups.

RESULTS

A total of 12 increased metabolites common to all MPS types were identified. Dipeptides, amino acids and derivatives were increased in the MPS group compared to controls. N-acetylgalactosamines 4- or 6-sulfate, important constituents of GAGs, were also elevated in MPS patients, most prominently in those with MPS VI. Notably, treated patients exhibited lower levels of the aforementioned acylaminosugars than untreated patients in all MPS types.

CONCLUSIONS

Untargeted metabolomics has enabled the detection of metabolites that could improve our understanding of MPS physiopathology. These potential biomarkers can be utilized in screening methods to support diagnosis and ERT monitoring.

Benchmarking Outlier Detection Methods for Detecting IEM Patients in Untargeted Metabolomics Data

Untargeted metabolomics (UM) is increasingly being deployed as a strategy for screening patients that are suspected of having an inborn error of metabolism (IEM). In this study, we examined the potential of existing outlier detection methods to detect IEM patient profiles. We benchmarked 30 different outlier detection methods when applied to three untargeted metabolomics datasets. Our results show great differences in IEM detection performances across the various methods. The methods DeepSVDD and R-graph performed most consistently across the three metabolomics datasets. For datasets with a more balanced number of samples-to-features ratio, we found that AE reconstruction error, Mahalanobis and PCA reconstruction error also performed well. Furthermore, we demonstrated the importance of a PCA transform prior to applying an outlier detection method since we observed that this increases the performance of several outlier detection methods. For only one of the three metabolomics datasets, we observed clinically satisfying performances for some outlier detection methods, where we were able to detect 90% of the IEM patient samples while detecting no false positives. These results suggest that outlier detection methods have the potential to aid the clinical investigator in routine screening for IEM using untargeted metabolomics data, but also show that further improvements are needed to ensure clinically satisfying performances.

A narrative review of metabolomics in the era of "-omics": integration into clinical practice for inborn errors of metabolism

BACKGROUND AND OBJECTIVE

Traditional targeted metabolomic investigations identify a pre-defined list of analytes in samples and have been widely used for decades in the diagnosis and monitoring of inborn errors of metabolism (IEMs). Recent technological advances have resulted in the development and maturation of untargeted metabolomics: a holistic, unbiased, analytical approach to detecting metabolic disturbances in human disease. We aim to provide a summary of untargeted metabolomics [focusing on tandem mass spectrometry (MS-MS)] and its application in the field of IEMs.

METHODS

Data for this review was identified through a literature search using PubMed, Google Scholar, and personal repositories of articles collected by the authors. Findings are presented within several sections describing the metabolome, the current use of targeted metabolomics in the diagnostic pathway of patients with IEMs, the more recent integration of untargeted metabolomics into clinical care, and the limitations of this newly employed analytical technique.

KEY CONTENT AND FINDINGS

Untargeted metabolomic investigations are increasingly utilized in screening for rare disorders, improving understanding of cellular and subcellular physiology, discovering novel biomarkers, monitoring therapy, and functionally validating genomic variants. Although the untargeted metabolomic approach has some limitations, this "next generation metabolic screening" platform is becoming increasingly affordable and accessible.

CONCLUSIONS

When used in conjunction with genomics and the other promising "-omic" technologies, untargeted metabolomics has the potential to revolutionize the diagnostics of IEMs (and other rare disorders), improving both clinical and health economic outcomes.

Understanding Inborn Errors of Metabolism through Metabolomics

Inborn errors of metabolism (IEMs) are rare diseases caused by a defect in a single enzyme, co-factor, or transport protein. For most IEMs, no effective treatment is available and the exact disease mechanism is unknown. The application of metabolomics and, more specifically, tracer metabolomics in IEM research can help to elucidate these disease mechanisms and hence direct novel therapeutic interventions. In this review, we will describe the different approaches to metabolomics in IEM research. We will discuss the strengths and weaknesses of the different sample types that can be used (biofluids, tissues or cells from model organisms; modified cell lines; and patient fibroblasts) and when each of them is appropriate to use.

Mucopolysaccharidosis Type VI, an Updated Overview of the Disease

Mucopolysaccharidosis type VI, or Maroteaux-Lamy syndrome, is a rare, autosomal recessive genetic disease, mainly affecting the pediatric age group. The disease is due to pathogenic variants of the ARSB gene, coding for the lysosomal hydrolase N-acetylgalactosamine 4-sulfatase (arylsulfatase B, ASB). The enzyme deficit causes a pathological accumulation of the undegraded glycosaminoglycans dermatan-sulphate and chondroitin-sulphate, natural substrates of ASB activity. Intracellular and extracellular deposits progressively take to a pathological scenario, often severe, involving most organ-systems and generally starting from the osteoarticular apparatus. Neurocognitive and behavioral abilities, commonly described as maintained, have been actually investigated by few studies. The disease, first described in 1963, has a reported prevalence between 0.36 and 1.3 per 100,000 live births across the continents. With this paper, we wish to contribute an updated overview of the disease from the clinical, diagnostic, and therapeutic sides. The numerous in vitro and in vivo preclinical studies conducted in the last 10-15 years to dissect the disease pathogenesis, the efficacy of the available therapeutic treatment (enzyme replacement therapy), as well as new therapies under study are here described. This review also highlights the need to identify new disease biomarkers, potentially speeding up the diagnostic process and the monitoring of therapeutic efficacy.

Disruption of morphogenic and growth pathways in lysosomal storage diseases

The lysosome achieved a new protagonism that highlights its multiple cellular functions, such as in the catabolism of complex substrates, nutrient sensing, and signaling pathways implicated in cell metabolism and growth. Lysosomal storage diseases (LSDs) cause lysosomal accumulation of substrates and deficiency in trafficking of macromolecules. The substrate accumulation can impact one or several pathways which contribute to cell damage. Autophagy impairment and immune response are widely studied, but less attention is paid to morphogenic and growth pathways and its impact on the pathophysiology of LSDs. Hedgehog pathway is affected with abnormal expression and changes in distribution of protein levels, and a reduced number and length of primary cilia. Moreover, growth pathways are identified with delay in reactivation of mTOR that deregulate termination of autophagy and reformation of lysosomes. Insulin resistance caused by changes in lipids rafts has been described in different LSDs. While the genetic and biochemical bases of deficient proteins in LSDs are well understood, the secondary molecular mechanisms that disrupt wider biological processes associated with LSDs are only now becoming clearer. Therefore, we explored how specific signaling pathways can be related to specific LSDs, showing that a system medicine approach could be a valuable tool for the better understanding of LSD pathogenesis. This article is categorized under: Metabolic Diseases > Molecular and Cellular Physiology.

Detecting lysosomal storage disorders by glycomic profiling using liquid chromatography mass spectrometry

BACKGROUND

Urine and plasma biomarker testing for lysosomal storage disorders by liquid chromatography mass spectrometry (LC-MS) currently requires multiple analytical methods to detect the abnormal accumulation of oligosaccharides, mucopolysaccharides, and glycolipids. To improve clinical testing efficiency, we developed a single LC-MS method to simultaneously identify disorders of oligosaccharide, mucopolysaccharide, and glycolipid metabolism with minimal sample preparation.

METHODS

We created a single chromatographic method for separating free glycans and glycolipids in their native form, using an amide column and high pH conditions. We used this glycomic profiling method both in untargeted analyses of patient and control urines using LC ion-mobility high-resolution MS (biomarker discovery), and targeted analyses of urine, serum, and dried blood spot samples by LC-MS/MS (clinical validation).

RESULTS

Untargeted glycomic profiling revealed twenty biomarkers that could identify and subtype mucopolysaccharidoses. We incorporated these with known oligosaccharide and glycolipid biomarkers into a rapid test that identifies at least 27 lysosomal storage disorders, including oligosaccharidoses, mucopolysaccharidoses, sphingolipidoses, glycogen storage disorders, and congenital disorders of glycosylation and de-glycosylation. In a validation set containing 115 urine samples from patients with lysosomal storage disorders, all were unambiguously distinguished from normal controls, with correct disease subtyping for 88% (101/115) of cases. Glucosylsphingosine was reliably elevated in dried blood spots from Gaucher disease patients with baseline resolution from galactosylsphingosine.

CONCLUSION

Glycomic profiling by liquid chromatography mass spectrometry identifies a range of lysosomal storage disorders. This test can be used in clinical evaluations to rapidly focus a diagnosis, as well as to clarify or support additional gene sequencing and enzyme studies.

The rapidly evolving view of lysosomal storage diseases

Lysosomal storage diseases are a group of metabolic disorders caused by deficiencies of several components of lysosomal function. Most commonly affected are lysosomal hydrolases, which are involved in the breakdown and recycling of a variety of complex molecules and cellular structures. The understanding of lysosomal biology has progressively improved over time. Lysosomes are no longer viewed as organelles exclusively involved in catabolic pathways, but rather as highly dynamic elements of the autophagic-lysosomal pathway, involved in multiple cellular functions, including signaling, and able to adapt to environmental stimuli. This refined vision of lysosomes has substantially impacted on our understanding of the pathophysiology of lysosomal disorders. It is now clear that substrate accumulation triggers complex pathogenetic cascades that are responsible for disease pathology, such as aberrant vesicle trafficking, impairment of autophagy, dysregulation of signaling pathways, abnormalities of calcium homeostasis, and mitochondrial dysfunction. Novel technologies, in most cases based on high-throughput approaches, have significantly contributed to the characterization of lysosomal biology or lysosomal dysfunction and have the potential to facilitate diagnostic processes, and to enable the identification of new therapeutic targets.

Lipid changes in the metabolome of a single case study with maple syrup urine disease (MSUD) after five days of improved diet adherence of controlled branched-chain amino acids (BCAA)

Background

Distinguishing systemic metabolic disruptions in maple syrup urine disease (MSUD) beyond amino acid pathways is under-investigated, yet important to understanding disease pathology and treatment options.

Methods

An adolescent female (15 years) with MSUD without liver transplant, attended 2 study visits, 5 days apart. Medical diet adherence was determined based on her 3-day diet records and plasma branched-chain amino acid (BCAA) concentrations at both study visits. Plasma from a single age- and sex-matched control (MURDOCK Study, Duke University) and the case patient were analyzed with UPLC/MS/MS for intensity (m/z), annotated, and normalized against a median of 1 (Metabolon, Morrisville NC). Differences between case/control and 5-day comparisons were defined as ≥ ǀ 0.5 ǀ.

Results

434 lipid metabolites were identified across samples; 90 (20.7%) were higher and 120 (27.6%) lower in the MSUD case at baseline compared with control. By study visit 2, plasma BCAA had declined, while 48 (53%) of elevated lipids and 14 (11.7%) of lower lipid values had moved to within ǀ 0.5 ǀ of control. Most shifts towards control by day 5 were seen in long-chain fatty acid intermediates (42%) and acylcarnitines (32%). Although androgenic (28%) and bile acid (23%) metabolites increased towards control, neither reached control level by day 5.

Discussion

This comparative metabolomics study in a single MSUD case and healthy control suggests intrinsic differences in MSUD lipid metabolism potentially influenced by therapeutic diet. Findings suggest influences on hormone regulation, fatty acid oxidation, and bile acid synthesis, but further studies are needed to confirm an association between MSUD and lipid dysregulation.

Synopsis

Within 5 days of improved dietary adherence, a single MSUD case experienced substantial changes in lipid markers potentially related to changes in plasma branched-chain amino acids.

Novel biomarkers for lysosomal storage disorders: Metabolomic and proteomic approaches

Lysosomal storage disorders (LSDs) are characterized by the accumulation of specific disease substrates inside the lysosomes of various cells, eventually leading to the deterioration of cellular function and multisystem organ damage. With the continuous discovery and validation of novel and advanced therapies for most LSDs, there is an urgent need to discover more versatile and clinically relevant biomarkers. The utility of these biomarkers should ideally extend beyond the screening and diagnosis of LSDs to the evaluation of disease severity and monitoring of therapy. Metabolomic and proteomic approaches provide the means to the discovery and validation of such novel biomarkers. This is achieved mainly through the application of various mass spectrometric techniques to common and easily accessible biological samples, such as plasma, urine and dried blood spots. In this review, we tried to summarize the complexity of the lysosomal disorders phenotypes, their current diagnostic and therapeutic approaches, the various techniques supporting metabolomic and proteomic studies and finally we tried to explore the newly discovered biomarkers for most LSDs and their reported clinical values.

Targeted Metabolomic Analysis of a Mucopolysaccharidosis IIIB Mouse Model Reveals an Imbalance of Branched-Chain Amino Acid and Fatty Acid Metabolism

Mucopolysaccharidoses (MPSs) are inherited disorders of the glycosaminoglycan (GAG) metabolism. The defective digestion of GAGs within the intralysosomal compartment of affected patients leads to a broad spectrum of clinical manifestations ranging from cardiovascular disease to neurological impairment. The molecular mechanisms underlying the progression of the disease downstream of the genetic mutation of genes encoding for lysosomal enzymes still remain unclear. Here, we applied a targeted metabolomic approach to a mouse model of PS IIIB, using a platform dedicated to the diagnosis of inherited metabolic disorders, in order to identify amino acid and fatty acid metabolic pathway alterations or the manifestations of other metabolic phenotypes. Our analysis highlighted an increase in the levels of branched-chain amino acids (BCAAs: Val, Ile, and Leu), aromatic amino acids (Tyr and Phe), free carnitine, and acylcarnitines in the liver and heart tissues of MPS IIIB mice as compared to the wild type (WT). Moreover, Ala, Met, Glu, Gly, Arg, Orn, and Cit amino acids were also found upregulated in the liver of MPS IIIB mice. These findings show a specific impairment of the BCAA and fatty acid catabolism in the heart of MPS IIIB mice. In the liver of affected mice, the glucose-alanine cycle and urea cycle resulted in being altered alongside a deregulation of the BCAA metabolism. Thus, our data demonstrate that an accumulation of BCAAs occurs secondary to lysosomal GAG storage, in both the liver and the heart of MPS IIIB mice. Since BCAAs regulate the biogenesis of lysosomes and autophagy mechanisms through mTOR signaling, impacting on lipid metabolism, this condition might contribute to the progression of the MPS IIIB disease.