Focus: Rare Disease: Neuromonitoring in Rare Disorders of Metabolism

Inborn errors of metabolism (IEM) are a unique class of genetic diseases due to mutations in genes involved in key metabolic pathways. The combined incidence of IEM has been estimated to be as high as 1:1000. Urea Cycle disorders (UCD), one class of IEM, can present with cerebral edema and represent a possible target to explore the utility of different neuromonitoring techniques during an hyperammonemic crisis. The last two decades have brought advances in the early identification and comprehensive management of UCD, including further understanding of neuroimaging patterns associated with neurocognitive function. Nonetheless, very important questions remain about the potential acute neurotoxic effects of hyperammonemia to better understand how to treat and prevent secondary brain injury. In this review, we describe existing neuromonitoring techniques that have been used in rare metabolic disorders to assess and allow amelioration of ongoing brain injury. Directions of future research should be focused on identifying new diagnostic approaches in the management of metabolic crises to optimize care and reduce long term morbidity and mortality in patients with IEM.     

Geistige Behinderung infolge Stoffwechselkrankheit

Inborn errors of metabolism (IEM) are rare causes of mental retardation (MR) and constitute about 1% of all cases of MR in the Caucasian population. In contrast to recommendations for other diagnostic laboratory tests in MR, e.g. chromosome analysis, there is no consensus on criteria for metabolic testing. IEM, however, are potentially treatable and their timely diagnosis is of relevance for prognosis, recurrence risk and the possibility of prenatal diagnosis. On the basis of current evidence, the following important IEM leading to nonspecific MR or to conditions with MR as the predominant clinical presentation are highlighted: creatine deficiency syndromes (in particular creatine transporter deficiency), mucopolysaccharidoses III (in particular IIIB), β-mannosidosis, specific organic acidurias, homocystinuria, CDG (congenital disorder of glycosylation), and specific disorders of purine and pyrimidine metabolism. In addition, urea cycle disorders, sterol synthesis defects and additional aminoacidurias are briefly considered. A rationale for metabolic testing in unexplained MR is presented.     

COVID-19 impact on the diagnosis of Inborn Errors of Metabolism: Data from a reference center in Brazil

The COVID-19 pandemic led to the reorganization of health care in several countries, including Brazil. Inborn Errors of Metabolism (IEM) are a group of rare and difficult to diagnose genetic diseases caused by pathogenic variants in genes that code for enzymes, cofactors, or structural proteins affecting different metabolic pathways. The aim of this study was to evaluate how COVID-19 affected the diagnosis of patients with IEM during the first year of the pandemic in Brazil comparing two distinct periods: from March 1^st, 2019 to February 29^th, 2020 (TIME A) and from March 1^st, 2020 to February 28^th, 2021 (TIME B), by the analysis of the number of tests and diagnoses performed in a Reference Center in South of Brazil. In the comparison TIME A with TIME B, we observe a reduction in the total number of tests performed (46%) and in the number of diagnoses (34%). In both periods analyzed, mucopolysaccharidoses (all subtypes combined) was the most frequent LD suspected and/or confirmed. Our data indicates a large reduction in the number of tests requested for the investigation of IEM and consequently a large reduction in the number of diagnoses caused by the COVID-19 pandemic leading to a significant underdiagnosis of IEM.     

Rapid pulsed whole genome sequencing for comprehensive acute diagnostics of inborn errors of metabolism

Background

Massively parallel DNA sequencing (MPS) has the potential to revolutionize diagnostics, in particular for monogenic disorders. Inborn errors of metabolism (IEM) constitute a large group of monogenic disorders with highly variable clinical presentation, often with acute, nonspecific initial symptoms. In many cases irreversible damage can be reduced by initiation of specific treatment, provided that a correct molecular diagnosis can be rapidly obtained. MPS thus has the potential to significantly improve both diagnostics and outcome for affected patients in this highly specialized area of medicine.

Results

We have developed a conceptually novel approach for acute MPS, by analysing pulsed whole genome sequence data in real time, using automated analysis combined with data reduction and parallelization. We applied this novel methodology to an in-house developed customized work flow enabling clinical-grade analysis of all IEM with a known genetic basis, represented by a database containing 474 disease genes which is continuously updated. As proof-of-concept, two patients were retrospectively analysed in whom diagnostics had previously been performed by conventional methods. The correct disease-causing mutations were identified and presented to the clinical team after 15 and 18 hours from start of sequencing, respectively. With this information available, correct treatment would have been possible significantly sooner, likely improving outcome.

Conclusions

We have adapted MPS to fit into the dynamic, multidisciplinary work-flow of acute metabolic medicine. As the extent of irreversible damage in patients with IEM often correlates with timing and accuracy of management in early, critical disease stages, our novel methodology is predicted to improve patient outcome. All procedures have been designed such that they can be implemented in any technical setting and to any genetic disease area. The strategy conforms to international guidelines for clinical MPS, as only validated disease genes are investigated and as clinical specialists take responsibility for translation of results. As follow-up in patients without any known IEM, filters can be lifted and the full genome investigated, after genetic counselling and informed consent.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1090) contains supplementary material, which is available to authorized users.     

Aminoacidopathies: Prevalence,Etiology, Screening,and Treatment Options

Inborn errors of metabolism (IEMs) are a group of inherited metabolic disorders which are caused by mutations in the specific genes that lead to impaired proteins or enzymes production. Different metabolic pathways are perturbed due to the deficiency or lack of enzymes. To date, more than 500 IEMs have been reported with most of them being untreatable. However, fortunately 91 such disorders are potentially treatable, if diagnosed at an earlier stage of life. IEMs have been classified into different categories and one class of IEMs, characterized by the physiological disturbances of amino acids is called as aminoacidopathies. Out of 91 treatable IEM, thirteen disorders are amino acid related. Aminoacidopathies can be detected by chromatography and mass spectrometry based analytical techniques (e.g., HPLC, GC–MS, LC–MS/MS) for amino acid level changes, and through genetic assays (e.g., PCR, TaqMan Genotyping, DNA sequencing) at the mutation level in the corresponding genes. Hence, this review is focused to describe thirteen common aminoacidopathies namely: Phenylketonuria (PKU), Maple Syrup Urine Disease (MSUD), Homocystinuria/Methylene Tetrahydrofolate Reductase (MTHFR) deficiency, Tyrosinemia type II, Citrullinemia type I and type II, Argininosuccinic aciduria, Carbamoyl Phosphate Synthetase I (CPS) deficiency, Argininemia (arginase deficiency), Hyperornithinemia–Hyperammonemia–Homocitrullinuria (HHH) syndrome, N-Acetylglutamate Synthase (NAGS) deficiency, Ornithine Transcarbamylase (OTC) deficiency, and Pyruvate Dehydrogenase (PDH) complex deficiency. Furthermore, the etiology, prevalence and commonly used analytical techniques for screening of aminoacidopathies are briefly described. This information would be helpful to researchers and clinicians especially from developing countries to initiate newborn screening programs for aminoacidopathies.     

Robustness of prevalence estimates derived from misclassified data from administrative databases

Because primary data collection can be expensive, researchers are increasingly using information collected in medical administrative databases for scientific purposes. This information, however, is typically collected for reasons other than research, and many such databases have been shown to contain substantial proportions of misclassification errors. For example, many administrative databases contain fields for patient diagnostic codes, but these are often missing or inaccurate, in part because physician reimbursement schemes depend on medical acts performed rather than any diagnosis. Errors in ascertaining which individuals have a given disease bias not only prevalence estimates, but also estimates of associations between the disease and other variables, such as medication use. We attempt to estimate the prevalence of osteoarthritis (OA) among elderly Quebeckers using a government administrative database. We compare a naive estimate relying solely on the physician diagnoses of OA listed in the database to estimates from several different Bayesian latent class models which adjust for misclassified physician diagnostic codes via use of other available diagnostic clues. We find that the prevalence estimates vary widely, depending on the model used and assumptions made. We conclude that any inferences from these databases need to be interpreted with great caution, until further work estimating the reliability of database items is carried out.     

X-linked recessive chondrodysplasia punctata with XY translocation in a stillborn fetus

Summary A case of X-linked recessive chondrodysplasia punctata (CP) is described. The finding of a reciprocal X-Y translocation involving the region distal to Xp22.3 and the presence of fluorescent Yp11.23 regions confirms the localization of X-linked recessive CP at p22.3. No gross peroxisomal abnormalities were present in the propositus.Part of this work was presented at the V International Congress on Inborn Errors of Metabolism, Asilomar, California, USA, 1990     

Nijmegen breakage syndrome (NBS)

Most inborn errors of metabolism (IEM) are recessive, genetically transmitted diseases and are classified into 3 main groups according to their mechanisms: cellular intoxication, energy deficiency, and defects of complex molecules. They can be associated with endocrine manifestations, which may be complications from a previously diagnosed IEM of childhood onset. More rarely, endocrinopathies can signal an IEM in adulthood, which should be suspected when an endocrine disorder is associated with multisystemic involvement (neurological, muscular, hepatic features, etc.). IEM can affect all glands, but diabetes mellitus, thyroid dysfunction and hypogonadism are the most frequent disorders. A single IEM can present with multiple endocrine dysfunctions, especially those involving energy deficiency (respiratory chain defects), and metal (hemochromatosis) and storage disorders (cystinosis). Non-autoimmune diabetes mellitus, thyroid dysfunction and/or goiter and sometimes hypoparathyroidism should steer the diagnosis towards a respiratory chain defect. Hypogonadotropic hypogonadism is frequent in haemochromatosis (often associated with diabetes), whereas primary hypogonadism is reported in Alstr?m disease and cystinosis (both associated with diabetes, the latter also with thyroid dysfunction) and galactosemia. Hypogonadism is also frequent in X-linked adrenoleukodystrophy (with adrenal failure), congenital disorders of glycosylation, and Fabry and glycogen storage diseases (along with thyroid dysfunction in the first 3 and diabetes in the last). This is a new and growing field and is not yet very well recognized in adulthood despite its consequences on growth, bone metabolism and fertility. For this reason, physicians managing adult patients should be aware of these diagnoses.     

CIDeR: multifactorial interaction networks in human diseases

ABSTRACT: The pathobiology of common diseases is influenced by heterogeneous factors interacting in complex networks. CIDeR http://mips.helmholtz-muenchen.de/cider/ is a publicly available, manually curated, integrative database of metabolic and neurological disorders. The resource provides structured information on 18,813 experimentally validated interactions between molecules, bioprocesses and environmental factors extracted from the scientific literature. Systematic annotation and interactive graphical representation of disease networks make CIDeR a versatile knowledge base for biologists, analysis of large-scale data and systems biology approaches.     

Antibiotic Resistance Genes Online (ARGO): a Database on vancomycin and beta-lactam resistance genes

Vancomycin and beta-lactams are antibiotics that inhibit gram positive bacteria by interfering with cell wall synthesis. However, continuous use of antibiotics results in the emergence of multi-drug resistant (MDR) bacterial strains. Here, we describe ARGO, a database containing gene sequences conferring resistance to these two classes of antibiotics. It is designed as a resource to enhance research on the prevalence and spread of antibiotic resistance genes. ARGO is the first attempt to compile the resistance gene sequence data with state specific information. AVAILABILITY: AGRO is available for free at http://www.argodb.org/     

The iterative ensemble modelling approach increases the accuracy of fish distribution models

Methodological absences, i.e. when a species is not detected although it is actually present, are known to reduce the prediction accuracy of species distribution models (SDMs). To deal with this problem, we assessed whether a new iterative ensemble modelling (IEM) approach better predicts the spatial distribution of a set of 31 freshwater fish species, exhibiting a wide range of prevalence and methodological absences. Model efficiency was compared using one threshold‐independent (AUC) and three threshold‐dependent indicators of model predictive performance: the percentage of misclassified sites; the Kappa index; and the True Skill Statistic. We then reconstructed species assemblages from individual species predictions and compared observed assemblages to those predicted using EM and IEM using the Jaccard index. Compared to an EM approach, IEM improved model predictive performance for most difficult‐to‐detect species. The iterative approach outperformed EM at modelling the distribution of difficult‐to‐detect species, provided that presence data are representative of the niche of the species. At the assemblage level, the discrepancy between observed and IEM predicted assemblages was significantly lower than that between observed and EM predicted assemblages, showing that IEM can be used to predict the distribution of entire species assemblages. The IEM approach provides a way to consider difficult‐to‐detect species in species distribution models.     

Screening for inborn errors of metabolism using gas chromatography–mass spectrometry

Screening of newborns for inborn errors of metabolism (IEM) in China is both a challenging and undeveloped area for gynecologists and pediatricians. Since 1999, the Capital Institute of Pediatrics has been studied as regards screening for IEM using advanced gas chromatography–mass spectrometry (GC–MS) method in collaboration with the Matsumoto Institute of Life Science (MILS), Japan, and has successfully diagnosed 51 cases of IEM in a total of 393 patients. Galactosemia, phenylketonuria and methylmalonic acidemia were the most frequent disorders among 51 cases of IEM. Treatment by suitable drugs and/or diet therapy was very effective in the most cases.     

Pilot study of gas chromatographic–mass spectrometric screening of newborn urine for inborn errors of metabolism after treatment with urease

Gas chromatographic–mass spectrometric (GC–MS) techniques for urinary organic acid profiling have been applied to high-risk screening for a wide range of diseases, mainly for inborn errors of metabolism (IEM), rather than to low-risk screening or mass screening. Using a simplified procedure with urease-pretreatment and the GC–MS technique, which allows simultaneous determination of organic acids, amino acids, sugars and sugar acids, we performed a pilot study of the application of this procedure to neonatal urine screening for 22 IEM. Out of 16 246 newborns screened, 11 cases of metabolic disorders were chemically diagnosed: two each of methylmalonic aciduria and glyceroluria, four of cystinuria, and one each of Hartnup disease, citrullinemia and α-aminoadipic aciduria/α-ketoadipic aciduria. The incidence of IEM was thus one per 1477, which was higher than the one per 3000 obtained in the USA in a study targeting amino acids and acylcarnitines in newborn blood spots by tandem mass spectrometry. Also, 227 cases were found to have transient metabolic abnormalities: 108 cases with neonatal tyrosinuria, 99 cases with neonatal galactosuria, and 20 cases with other transient metabolic disorders. Two hundred and thirty-eight cases out of 16 246 neonates (approximately 1/68) were thus diagnosed using this procedure as having either persistent or transient metabolic abnormalities.     

Genomes OnLine Database (GOLD): a monitor of genome projects world-wide

GOLD is a comprehensive resource for accessing information related to completed and ongoing genome projects world-wide. The database currently provides information on 350 genome projects, of which 48 have been completely sequenced and their analysis published. GOLD was created in 1997 and since April 2000 it has been licensed to Integrated Genomics. The database is freely available through the URL: http://igweb.integratedgenomics.com/GOLD/.     

Do musicians with perfect pitch have more autism traits than musicians without perfect pitch? An empirical study

Perfect pitch, also known as absolute pitch (AP), refers to the rare ability to identify or produce a musical tone correctly without the benefit of an external reference. AP is often considered to reflect musical giftedness, but it has also been associated with certain disabilities due to increased prevalence of AP in individuals with sensory and developmental disorders. Here, we determine whether individual autistic traits are present in people with AP. We quantified subclinical levels of autism traits using the Autism-Spectrum Quotient (AQ) in three matched groups of subjects: 16 musicians with AP (APs), 18 musicians without AP (non-APs), and 16 non-musicians. In addition, we measured AP ability by a pitch identification test with sine wave tones and piano tones. We found a significantly higher degree of autism traits in APs than in non-APs and non-musicians, and autism scores were significantly correlated with pitch identification scores (r = .46, p = .003). However, our results showed that APs did not differ from non-APs on diagnostically crucial social and communicative domain scores and their total AQ scores were well below clinical thresholds for autism. Group differences emerged on the imagination and attention switching subscales of the AQ. Thus, whilst these findings do link AP with autism, they also show that AP ability is most strongly associated with personality traits that vary widely within the normal population.     

Inborn errors of metabolism: the flux from Mendelian to complex diseases

Inborn errors of metabolism are characterized by dysregulation of the metabolic networks that underlie development and homeostasis, and constitute an important and expanding group of genetic disorders in humans. Diagnostic methods that are based on molecular genetic tools have a limited ability to correlate phenotypes with subtle changes in metabolic fluxes. We argue that the direct and dynamic measurement of metabolite flux will facilitate the integration of environmental, genetic and biochemical factors with phenotypic information. Ultimately, this integration will lead to new diagnostic and therapeutic approaches that are focused on the manipulation of these pathways.     

YPL.db: the Yeast Protein Localization database

The Yeast Protein Localization database (YPL.db) contains information about the localization patterns of yeast proteins resulting from microscopic analyses. The data and parameters of the experiments to obtain the localization information, together with images from confocal or video microscopy, are stored in a relational database, building an archive of, and the documentation for, all experiments. The database can be queried based on gene name, protein localization, growth conditions and a number of additional parameters. All experiment parameters are selectable from predefined lists to ensure database integrity and conformity across different investigators. The database provides a structure reference resource to allow for better characterization of unknown or ambiguous localization patterns. Links to MIPS, YPD and SGD databases are provided to allow fast access to further information not contained in the localization database itself. YPL.db is available at http://ypl.tugraz.at.     

A compendium of inborn errors of metabolism mapped onto the human metabolic network

Inborn errors of metabolism (IEMs) are hereditary metabolic defects, which are encountered in almost all major metabolic pathways occurring in man. Many IEMs are screened for in neonates through metabolomic analysis of dried blood spot samples. To enable the mapping of these metabolomic data onto the published human metabolic reconstruction, we added missing reactions and pathways involved in acylcarnitine (AC) and fatty acid oxidation (FAO) metabolism. Using literary data, we reconstructed an AC/FAO module consisting of 352 reactions and 139 metabolites. When this module was combined with the human metabolic reconstruction, the synthesis of 39 acylcarnitines and 22 amino acids, which are routinely measured, was captured and 235 distinct IEMs could be mapped. We collected phenotypic and clinical features for each IEM enabling comprehensive classification. We found that carbohydrate, amino acid, and lipid metabolism were most affected by the IEMs, while the brain was the most commonly affected organ. Furthermore, we analyzed the IEMs in the context of metabolic network topology to gain insight into common features between metabolically connected IEMs. While many known examples were identified, we discovered some surprising IEM pairs that shared reactions as well as clinical features but not necessarily causal genes. Moreover, we could also re-confirm that acetyl-CoA acts as a central metabolite. This network based analysis leads to further insight of hot spots in human metabolism with respect to IEMs. The presented comprehensive knowledge base of IEMs will provide a valuable tool in studying metabolic changes involved in inherited metabolic diseases.     

EuSplice: a unified resource for the analysis of splice signals and alternative splicing in eukaryotic genes

MOTIVATION: Despite increased availability of genome annotation data, a comprehensive resource for in-depth analysis of splice signal distributions and alternative splicing (AS) patterns in eukaryote genomes is still lacking. To meet this need, we have developed EuSplice--a unique splice-centric database which provides reliable splice signal and AS information for 23 eukaryotes. RESULTS: The EuSplice database contains 95,822 AS events and 2.1 million splice signals associated with over 270,000 protein-coding genes. The intuitive, user-friendly EuSplice web interface has powerful data mining and graphics capabilities for inter-genomic comparative analysis of splice signals, putative cryptic splice sites and AS events. Moreover, the seamless integration of splicing data to extensive gene-specific annotations, such as homolog annotations, functional information, mutations and sequence details makes EuSplice a powerful one-stop information resource for investigating the molecular mechanisms of complex splicing events, disease associations and the evolution of splicing in eukaryotes. AVAILABILITY: http://66.170.16.154/EuSplice. SUPPLEMENTARY INFORMATION: Supplementary tables and figures at Bioinfo online.