Uraemic brainstem encephalopathy mimicking ocular myasthenia: a case report.

BACKGROUND: Uraemia causes a generalised encephalopathy as its most common neurological complication. Isolated brainstem uraemic encephalopathy is rare. We report a case of fatigable ptosis and complex ophthalmoplegia in brainstem uraemic encephalopathy. CASE PRESENTATION: A 22-year-old Sri Lankan man with end stage renal failure presented with acute onset diplopia and drooping of eyelids progressively worsening over one week. The patient had not complied with the prescribed renal replacement therapy which was planned to be initiated 5 months previously. On examination, his Glasgow coma scale score was 15/15, He had a fatigable asymmetrical bilateral ptosis. The ice-pack test was negative. There was a complex ophthalmoplegia with bilateral abduction failure and elevation failure of the right eye. The diplopia did not worsen with prolonged stare. The rest of the neurological examination was normal. Serum creatinine on admission was 21.81 mg/dl. The repetitive nerve stimulation did not show a decremental pattern. Magnetic resonance imaging (MRI) of the brain demonstrated diffuse midbrain and pontine oedema with T2 weighted/FLAIR hyperintensities. The patient was haemodialyzed on alternate days and his neurological deficits completely resolved by the end of the second week of dialysis. The follow up brain MRI done two weeks later demonstrated marked improvement of the brainstem oedema with residual T2 weighted/FLAIR hyperintensities in the midbrain. CONCLUSIONS: Uraemia may rarely cause an isolated brainstem encephalopathy mimicking ocular myasthenia, which resolves with correction of the uraemia.

Comprehensive metabolomics analysis reveals novel biomarkers and pathways in falsely suspected glutaric aciduria Type-1 newborns.

BACKGROUND: Glutaric aciduria type-1 (GA-1) is a rare metabolic disorder due to glutaryl coenzyme A dehydrogenase deficiency, causing elevated levels of glutaryl-CoA and its derivatives. GA-1 exhibits symptoms like macrocephaly, developmental delays, and movement disorders. Timely diagnosis through genetic testing and newborn screening is crucial. However, in some cases, transiently elevated level of glutarylcarnitine (C5DC) challenges accurate diagnosis, highlighting the need for alternative diagnostic methods, like mass spectrometry-based untargeted metabolomics, to identify additional biomarkers for distinguishing falsely suspected GA-1 from healthy newborns. METHODOLOGY: DBS samples from falsely suspected GA-1 newborns (n = 47) and matched control were collected through the NBS program. Untargeted metabolomics using liquid chromatography-high-resolution mass spectrometry (LC-HRMS) was performed to enable biomarker and pathway investigations for significantly altered metabolites. RESULTS: 582 and 546 were up- and down-regulated metabolites in transient GA-1. 155 endogenous metabolites displayed significant variations compared to the control group. Furthermore, our data identified novel altered metabolic biomarkers, such as N-palmitoylcysteine, heptacarboxyporphyrin, 3-hydroxylinoleoylcarnitine, and monoacylglyceride (MG) (0:0/20:1/0:0), along with perturbed metabolic pathways like sphingolipid and thiamine metabolism associated with the transient elevated C5DC levels in DBS samples. CONCLUSIONS: A distinct metabolic pattern linked to the transient C5DC elevation in newborns was reported to enhance the prediction of the falsely positive cases, which could help avoiding unnecessary medical treatments and minimizing the financial burdens in the health sector.

Fatal cervical myelopathy in a child with glutaric aciduria type 1.

We report the case of a Syrian female refugee with late diagnosis of glutaric aciduria type 1 characterised by massive axial hypotonia and quadriplegia who only started adequate diet upon arrival in Switzerland at the age of 4 years, after a strenuous migration journey. Soon after arrival, she died from an unexpected severe upper cervical myelopathy, heralded by acute respiratory distress after a viral infection. This was likely due to repeated strains on her hypotonic neck and precipitated by an orthotopic os odontoideum who led to atlanto-axial subluxation. This case reminds us not to omit handling patients with insufficient postural control and hypotonia with great care to avoid progressive cervical myelopathy.

Analysis of a second-tier test panel in dried blood spot samples using liquid chromatography-tandem mass spectrometry in Catalonia's newborn screening programme.

OBJECTIVES: Acylcarnitine and amino acid analyses of dried blood spot (DBS) samples using tandem mass spectrometry in newborn screening (NBS) programmes can generate false positive (FP) results. Therefore, implementation of second-tier tests (2TTs) using DBS samples has become increasingly important to avoid FPs. The most widely used 2TT metabolites include methylmalonic acid, 3-hydroxypropionic acid, methylcitric acid, and homocysteine. METHODS: We simultaneously measured 46 underivatised metabolites, including organic acids, acylglycine and acylcarnitine isomers, homocysteine, and orotic acid, in DBS samples using tandem mass spectrometry. To validate this method, we analysed samples from 147 healthy newborns, 160 patients with genetic disorders diagnosed via NBS, 20 patients with acquired vitamin B12 deficiency, 10 newborns receiving antibiotic treatment, and nine external quality control samples. RESULTS: The validation study revealed that 31 metabolites showed good analytical performance. Furthermore, this method detected key metabolites for all diseases associated with increased levels of the following acylcarnitines: C3, C4, C5, C4DC/C5OH, and C5DC. The sensitivity of this method to detect all diseases was 100 %, and the specificity was 74-99 %, except for glutaric aciduria type 1. This method can also be used to diagnose mitochondrial fatty acid ß-oxidation disorders (FAODs) and urea cycle defects (UCDs). CONCLUSIONS: We have described a 2TT panel of 31 metabolites in DBS samples based on an easy and rapid method without derivatisation. Its implementation allowed us to distinguish between different organic acidurias, some FAODs, and UCDs. This new strategy has increased the efficiency of our NBS programme by reducing FP and false negative results, second sample requests, and the time required for diagnosis.

Modeling Glutaric Aciduria Type I in human neuroblastoma cells recapitulates neuronal damage that can be rescued by gene replacement.

Glutaric Aciduria type I (GA1) is a rare neurometabolic disorder caused by mutations in the GDCH gene encoding for glutaryl-CoA dehydrogenase (GCDH) in the catabolic pathway of lysine, hydroxylysine and tryptophan. GCDH deficiency leads to increased concentrations of glutaric acid (GA) and 3-hydroxyglutaric acid (3-OHGA) in body fluids and tissues. These metabolites are the main triggers of brain damage. Mechanistic studies supporting neurotoxicity in mouse models have been conducted. However, the different vulnerability to some stressors between mouse and human brain cells reveals the need to have a reliable human neuronal model to study GA1 pathogenesis. In the present work we generated a GCDH knockout (KO) in the human neuroblastoma cell line SH-SY5Y by CRISPR/Cas9 technology. SH-SY5Y-GCDH KO cells accumulate GA, 3-OHGA, and glutarylcarnitine when exposed to lysine overload. GA or lysine treatment triggered neuronal damage in GCDH deficient cells. SH-SY5Y-GCDH KO cells also displayed features of GA1 pathogenesis such as increased oxidative stress vulnerability. Restoration of the GCDH activity by gene replacement rescued neuronal alterations. Thus, our findings provide a human neuronal cellular model of GA1 to study this disease and show the potential of gene therapy to rescue GCDH deficiency.

Compilation of Genotype and Phenotype Data in GCDH-LOVD for Variant Classification and Further Application.

Glutaric aciduria type 1 (GA-1) is a rare but treatable autosomal-recessive neurometabolic disorder of lysin metabolism caused by biallelic pathogenic variants in glutaryl-CoA dehydrogenase gene (GCDH) that lead to deficiency of GCDH protein. Without treatment, this enzyme defect causes a neurological phenotype characterized by movement disorder and cognitive impairment. Based on a comprehensive literature search, we established a large dataset of GCDH variants using the Leiden Open Variation Database (LOVD) to summarize the known genotypes and the clinical and biochemical phenotypes associated with GA-1. With these data, we developed a GCDH-specific variation classification framework based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines. We used this framework to reclassify published variants and to describe their geographic distribution, both of which have practical implications for the molecular genetic diagnosis of GA-1. The freely available GCDH-specific LOVD dataset provides a basis for diagnostic laboratories and researchers to further optimize their knowledge and molecular diagnosis of this rare disease.

Tagging EEG features within exam reports to quickly generate databases for research purposes.

OBJECTIVE: assess the effectiveness of a new method for classifying EEG recording features through the use of tags within reports. We present feature prevalence in a sample of patients with toxic-metabolic encephalopathy and discuss the advantages of this approach over existing classification systems. METHODS: during EEG report creation, tags reflecting background activity, epileptiform features and periodic discharges were selected according to the findings of each recording. Reports including the tags have been collected and processed by the EEG report parser script written in PHP language. The resulting spreadsheet was analysed to calculate the prevalence and type of EEG features in a sample group of patients with toxic-metabolic encephalopathy. RESULTS: tag checking and extraction were very little time-consuming processes. Considering 5784 EEG recordings performed either in inpatients or outpatients over 2 years, toxic-metabolic aetiology was tagged in 218 (3.8 %). The most frequent background feature was severe slowing (5-6 Hz frequency), occurring in 79 (36.2 %). Epileptiform abnormalities were rare, reaching a maximum of 10 (4.6 %). Triphasic waves were tagged in 43 (19.7 %) recordings. CONCLUSIONS: tagging and parsing processes are very fast and integrated into the daily routine. Sample analysis in patients with toxic-metabolic encephalopathies showed EEG slowing as the prevalent feature, while triphasic waves occurred in a minority of recordings. Existing software such as "SCORE" (Holberg EEG) requires the replacement of the currently used software for EEG reporting, minimizing additional costs and training. EEG Report Parser is free and open-source software, so it can be freely adopted, modified and redistributed, allowing further improvement and adaptability.

Glutaryl-CoA Dehydrogenase Misfolding in Glutaric Acidemia Type 1.

Glutaric acidemia type 1 (GA1) is a neurotoxic metabolic disorder due to glutaryl-CoA dehydrogenase (GCDH) deficiency. The high number of missense variants associated with the disease and their impact on GCDH activity suggest that disturbed protein conformation can affect the biochemical phenotype. We aimed to elucidate the molecular basis of protein loss of function in GA1 by performing a parallel analysis in a large panel of GCDH missense variants using different biochemical and biophysical methodologies. Thirteen GCDH variants were investigated in regard to protein stability, hydrophobicity, oligomerization, aggregation, and activity. An altered oligomerization, loss of protein stability and solubility, as well as an augmented susceptibility to aggregation were observed. GA1 variants led to a loss of enzymatic activity, particularly when present at the N-terminal domain. The reduced cellular activity was associated with loss of tetramerization. Our results also suggest a correlation between variant sequence location and cellular protein stability (p < 0.05), with a more pronounced loss of protein observed with variant proximity to the N-terminus. The broad panel of variant-mediated conformational changes of the GCDH protein supports the classification of GA1 as a protein-misfolding disorder. This work supports research toward new therapeutic strategies that target this molecular disease phenotype.

Update current understanding of neurometabolic disorders related to lysine metabolism.

Lysine, as an essential amino acid, predominantly undergoes metabolic processes through the saccharopine pathway, whereas a smaller fraction follows the pipecolic acid pathway. Although the liver is considered the primary organ for lysine metabolism, it is worth noting that lysine catabolism also takes place in other tissues and organs throughout the body, including the brain. Enzyme deficiency caused by pathogenic variants in its metabolic pathway may lead to a series of neurometabolic diseases, among which glutaric aciduria type 1 and pyridoxine-dependent epilepsy have the most significant clinical manifestations. At present, through research, we have a deeper understanding of the multiple pathophysiological mechanisms related to these diseases, including intracerebral accumulation of neurotoxic metabolites, imbalance between GABAergic and glutamatergic neurotransmission, energy deprivation due to metabolites, and the dysfunction of antiquitin. Because of the complexity of these diseases, their clinical manifestations are also diverse. The early implementation of lysine-restricted diets and supplementation with arginine and carnitine has reported positive impacts on the neurodevelopmental outcomes of patients. Presently, there is more robust evidence supporting the effectiveness of these treatments in glutaric aciduria type 1 compared with pyridoxine-dependent epilepsy.

Biochemical and molecular features of chinese patients with glutaric acidemia type 1 from Fujian Province, southeastern China.

BACKGROUND: Glutaric acidemia type 1 (GA1) is a rare autosomal recessive inherited metabolic disorder caused by variants in the gene encoding the enzyme glutaryl-CoA dehydrogenase (GCDH). The estimated prevalence of GA1 and the mutational spectrum of the GCDH gene vary widely according to race and region. The aim of this study was to assess the acylcarnitine profiles and genetic characteristics of patients with GA1 in Fujian Province, southeastern China. RESULTS: From January 2014 to December 2022, a total of 1,151,069 newborns (631,016 males and 520,053 females) were screened using MS/MS in six newborn screening (NBS) centers in Fujian Province and recruited for this study. Through NBS, 18 newborns (13 females and 5 males) were diagnosed with GA1. Thus, the estimated incidence of GA1 was 1 in 63,948 newborns in Fujian province. In addition, 17 patients with GA1 were recruited after clinical diagnosis. All but one patient with GA1 had a remarkable increase in glutarylcarnitine (C5DC) concentrations. The results of urinary organic acid analyses in 33 patients showed that the concentration of glutaric acid (GA) increased in all patients. The levels of C5DC and GA in patients identified via NBS were higher than those in patients identified via clinical diagnosis (P < 0.05). A total of 71 variants of 70 alleles were detected in patients with GA1, with 19 different pathogenic variants identified. The three most prevalent variants represented 73.23% of the total and were c.1244-2 A > C, p.(?) (63.38%), c.1261G > A, p.Ala421Thr (5.63%), and c.406G > T, p.Gly136Cys (4.22%). The most abundant genotype observed was c.[1244-2 A > C]; [1244-2 A > C] (18/35, 52.43%) and its phenotype corresponded to high excretors (HE, GA > 100 mmol/mol Cr). CONCLUSIONS: In conclusion, we investigated the biochemical and molecular features of 35 unrelated patients with GA1. C5DC concentrations in dried blood spots and urinary GA are effective indicators for a GA1 diagnosis. Our study also identified a GCDH variant spectrum in patients with GA1 from Fujian Province, southeastern China. Correlation analysis between genotypes and phenotypes provides preliminary and valuable information for genetic counseling and management.

Use of Thalamus L-Sign to Differentiate Periventricular Leukomalacia From Neurometabolic Disorders.

PURPOSE: To assess the diagnostic value of the thalamus L-sign on magnetic resonance imaging (MRI) in distinguishing between periventricular leukomalacia and neurometabolic disorders in pediatric patients. METHODS: In this retrospective study, clinical and imaging information was collected from 50 children with periventricular leukomalacia and 52 children with neurometabolic disorders. MRI was used to evaluate the L-sign of the thalamus (ie, injury to the posterolateral thalamus) and the lobar distribution of signal intensity changes. Age, sex, gestational age, and level of Gross Motor Function Classification System (only for periventricular leukomalacia) constituted the clinical parameters. Statistical evaluation of group differences for imaging and clinical variables were conducted using univariable statistical methods. The intra- and inter-observer agreement was evaluated using Cohen's kappa. Univariable or multivariable logistic regression was employed for selection of variables, determining independent predictors, and modeling. RESULTS: The thalamus L-sign was observed in 70% (35/50) of patients in the periventricular leukomalacia group, but in none of the patients with neurometabolic disorder (P < .001). The gestational age between groups varied significantly (P < .001). Involvement of frontal, parietal, and occipital lobes differed significantly between groups (P < .001). In the logistic regression, the best model included negative thalamus L-sign and gestational age, yielding an area under the curve, accuracy, sensitivity, specificity, and precision values of 0.995, 96.1%, 96%, 96.2%, and 96%, respectively. Both the lack of thalamus L-sign and gestational age were independent predictors (P < .001). CONCLUSIONS: The thalamus L-sign and gestational age may be useful in distinguishing between periventricular leukomalacia and neurometabolic disorders.

Exploring genotype-phenotype correlations in glutaric aciduria type 1.

Glutaric aciduria type 1 (GA1) is a rare neurometabolic disease caused by pathogenic variants in the gene encoding the enzyme glutaryl-CoA dehydrogenase (GCDH). We performed an extensive literature search to collect data on GA1 patients, together with unpublished cases, to provide an up-to-date genetic landscape of GCDH pathogenic variants and to investigate potential genotype-phenotype correlation, as this is still poorly understood. From this search, 421 different GCDH pathogenic variants have been identified, including four novel variants; c.179T>C (p.Leu60Pro), c.214C>T (p.Arg72Cys), c.309G>C (p.Leu103Phe), and c.665T>C (p.Phe222Ser).The variants are mostly distributed across the entire gene; although variant frequency in GA1 patients is relatively high in the regions encoding for active domains of GCDH. To investigate potential genotype-phenotype correlations, phenotypic descriptions of 532 patients have been combined and evaluated using novel combinatorial analyses. To do so, various clinical phenotypes were determined for each pathogenic variant by combining the information of all GA1 patients reported with this pathogenic variant, and subsequently mapped onto the 2D and 3D GCDH protein structure. In addition, the predicted pathogenicity of missense variants was analyzed using different in silico prediction score models. Both analyses showed an almost similar distribution of the highly pathogenic variants across the GCDH protein, although some hotspots, including the active domain, were observed. Moreover, it was demonstrated that highly pathogenic variants are significantly correlated with lower residual enzyme activity and the most accurate estimation was achieved by the REVEL score. A clear correlation of the genotype and the clinical phenotype however is still lacking.

Phenotypic prediction in glutaric aciduria type 1 combining in silico and in vitro modeling with real-world data.

Glutaric aciduria type 1 (GA1) is caused by inherited deficiency of glutaryl-CoA dehydrogenase (GCDH). To further understand the unclear genotype-phenotype correlation, we transfected mutated GCDH into COS-7 cells resembling known biallelic GCDH variants of 47 individuals with GA1. In total, we modeled 36 genotypes with 32 missense variants. Spectrophotometry demonstrated an inverse correlation between residual enzyme activity and the urinary concentration of glutaric acid and 3-hydroxyglutaric acid, confirming previous studies (Pearson correlation, r = -0.34 and r = -0.49, p = 0.045 and p = 0.002, respectively). In silico modeling predicted high pathogenicity for all genotypes, which caused a low enzyme activity. Western blotting revealed a 2.6-times higher GCDH protein amount in patients with an acute encephalopathic crisis (t-test, p = 0.015), and high protein expression correlated with high in silico protein stability (Pearson correlation, r = -0.42, p = 0.011). The protein amount was not correlated with the enzyme activity (Pearson correlation, r = 0.09, p = 0.59). To further assess protein stability, proteolysis was performed, showing that the p.Arg88Cys variant stabilized a heterozygous less stable variant. We conclude that an integration of different data sources helps to predict the complex clinical phenotype in individuals with GA1.

Generation of an induced pluripotent stem cell line carrying a biallelic deletion (SCTCi019-A) in GCDH using CRISPR/Cas9.

GCDH encodes for the enzyme catalyzing the sixth step of the lysine catabolism pathway. Biallelic pathogenic variants in GCDH have been associated with glutaric aciduria type 1 (GA1). In this study CRISPR/Cas9 technology was used to create an isogenic GCDH knock-out human iPSC line. One clone with a biallelic deletion (SCTCi019-A) in GCDH was obtained and fully characterized, revealing a normal karyotype, no off-targets detected and expression of pluripotency markers. This iPSC line can contribute to gain insights in the molecular mechanism of disease.

2-Methylglutaconic acid as a biomarker in routine urine organic acids leading to the diagnosis of glutaric acidemia type I in a low excretor.

GA1 (OMIM# 231670) is an organic aciduria caused by defective Glutaryl-CoA dehydrogenase (GCDH), encoded by GCDH. Early detection of GA1 is crucial to prevent patients from developing acute encephalopathic crisis and subsequent neurologic sequelae. Diagnosis of GA1 relies on elevated glutarylcarnitine (C5DC) in plasma acylcarnitine analysis and hyperexcretion of glutaric acid (GA) and 3-hydroxyglutaric acid (3HG) in urine organic acid (UOA) analysis. Low excretors (LE), however, exhibit subtly elevated or even normal plasma C5DC and urinary GA levels, leading to screening and diagnostic challenges. The measurement of 3HG in UOA is thus often used as the 1st tier test for GA1. We described a case of LE detected via newborn screen with normal excretion of GA, absent of 3HG and increased 2-methylglutaconic acid (2MGA), which was detected at 3 mg/g creatinine (reference interval <1 mg/g creatinine) without appreciable ketones. We retrospectively examined UOA of 8 other GA1 patients and the 2MGA level ranged from 2.5 to 27.39 mg/g creatinine, which is significantly higher than normal controls (0.05-1.61 mg/g creatinine). Although the underlying mechanism of 2MGA formation in GA1 is unclear, our study suggests 2MGA is a biomarker for GA1 and should be monitored by routine UOA to evaluate its diagnostic and prognostic value.