GAA compound heterozygous mutations associated with autophagic impairment cause cerebral infarction in Pompe disease

Mutations in Glycosyltransferases and Glycosidases: Implications for Associated Diseases

Glycosylation, a crucial and the most common post-translational modification, coordinates a multitude of biological functions through the attachment of glycans to proteins and lipids. This process, predominantly governed by glycosyltransferases (GTs) and glycoside hydrolases (GHs), decides not only biomolecular functionality but also protein stability and solubility. Mutations in these enzymes have been implicated in a spectrum of diseases, prompting critical research into the structural and functional consequences of such genetic variations. This study compiles an extensive dataset from ClinVar and UniProt, providing a nuanced analysis of 2603 variants within 343 GT and GH genes. We conduct thorough MTR score analyses for the proteins with the most documented variants using MTR3D-AF2 via AlphaFold2 (AlphaFold v2.2.4) predicted protein structure, with the analyses indicating that pathogenic mutations frequently correlate with Beta Bridge secondary structures. Further, the calculation of the solvent accessibility score and variant visualisation show that pathogenic mutations exhibit reduced solvent accessibility, suggesting the mutated residues are likely buried and their localisation is within protein cores. We also find that pathogenic variants are often found proximal to active and binding sites, which may interfere with substrate interactions. We also incorporate computational predictions to assess the impact of these mutations on protein function, utilising tools such as mCSM to predict the destabilisation effect of variants. By identifying these critical regions that are prone to disease-associated mutations, our study opens avenues for designing small molecules or biologics that can modulate enzyme function or compensate for the loss of stability due to these mutations.

Towards personalized genome-scale modeling of inborn errors of metabolism for systems medicine applications

Inborn errors of metabolism (IEMs) are a group of more than 1000 inherited diseases that are individually rare but have a cumulative global prevalence of 50 per 100,000 births. Recently, it has been recognized that like common diseases, patients with rare diseases can greatly vary in the manifestation and severity of symptoms. Here, we review omics-driven approaches that enable an integrated, holistic view of metabolic phenotypes in IEM patients. We focus on applications of Constraint-based Reconstruction and Analysis (COBRA), a widely used mechanistic systems biology approach, to model the effects of inherited diseases. Moreover, we review evidence that the gut microbiome is also altered in rare diseases. Finally, we outline an approach using personalized metabolic models of IEM patients for the prediction of biomarkers and tailored therapeutic or dietary interventions. Such applications could pave the way towards personalized medicine not just for common, but also for rare diseases.

Case Report: Identification of Compound Heterozygous Mutations in a Patient With Late-Onset Glycogen Storage Disease Type II (Pompe Disease)

Pompe disease is an autosomal recessive hereditary lysosomal disorder and correlated with acid α-glucosidase enzyme (GAA) deficiencies, which lead to accumulation of glycogen in all tissues, most notably in skeletal muscles. Adult late-onset Pompe disease (LOPD) is a slowly progressive disease of proximal myopathy with later involvement of the respiratory muscles, resulting in respiratory failure. In this study, we reported a 22-year-old Chinese woman with inability to withstand heavy physical activity since childhood, who presented with respiratory and ambulation weakness in 2 months. On admission, her bilateral upper limbs strength was 4/5 and lower limbs strength was 3/5 according to Medical Research Council (MRC) score. The patient had compound heterozygotes containing a newly identified 4 nt deletion of coding sequence (deletion nt 1411_1414) in one of the acid α-glucosidase alleles and a c.2238G>C (p.Trp746Cys) missense mutation. This deletion has been reported in infant-onset Pompe disease (IOPD) but not LOPD. Intriguingly, this deletion mutation was not found in the patient's family and was considered as pathogenic. Muscle biopsy showed scattered vacuoles with basophilic granules inside the subsarcolemmal area, which were strongly stained by periodic acid-Schiff (PAS). Laboratory tests revealed a significant increase of creatine kinase MB isoenzyme (CK-MB) and lactate dehydrogenase (LDH). GAA level was 9.77 nmol/1 h/mg and was not sufficient for the diagnosis of GAA activity deficiency (0–3.78 nmol/1 h/mg). In summary, mutational analysis of GAA and muscle biopsy are crucial in the diagnosis of Pompe disease.

Stroke and stroke-like episodes in inborn errors of metabolism: Pathophysiological and clinical implications

Inborn errors of metabolism causing stroke (ischemic or haemorrhagic) or stroke-like episodes (e.g., that are also called "metabolic strokes" and include acute brain lesions not related with alterations of blood flow) cover a wide range of diseases in which acute metabolic decompensations after trigger events (e.g., fever, dehydration, sepsis etc.) may have a variable frequency. The early diagnosis of these conditions is essential because, despite their rarity, effective symptomatic treatments may be available for acute settings (e.g., arginine for Mitochondrial myopathy, Encephalopathy, Lactic Acidosis, and Stroke-like episodes- MELAS) while in other cases disease modifying therapies may be useful to prevent stroke occurrence, recurrence, or relapse (e.g., Fabry disease). The detection of a non-vascular distribution of lesions and the diffuse use of ¹HMRS are often diriment in the differential of ischemic and metabolic strokes. This review summarized the main clinical features and the pathophysiological mechanisms of stroke and stroke-like episodes in inborn errors of metabolism presenting with stroke as part of natural history of the disease. These conditions belong to different etiological groups, such as organic acidurias, mitochondrial encephalopathies, homocystinuria and remethylation disorders, urea cycle disorders, lysosomal diseases (e.g. Fabry disease, glycogen storage disease), congenital disorders of glycosylation, neurotransmitter disorders, adenosine deaminase 2 deficiency and few other neurometabolic disorders.

An Integrated Autophagy-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics-Based Approach

Endometrial cancer is one of the most common malignant tumors, lowering the quality of life among women worldwide. Autophagy plays dual roles in these malignancies. To search for prognostic markers for endometrial cancer, we mined The Cancer Genome Atlas and the Human Autophagy Database for information on endometrial cancer and autophagy-related genes and identified five autophagy-related long noncoding RNAs (lncRNAs) (LINC01871, SCARNA9, SOS1-IT1, AL161618.1, and FIRRE). Based on these autophagy-related lncRNAs, samples were divided into high-risk and low-risk groups. Survival analysis showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group. Univariate and multivariate independent prognostic analyses showed that patients' age, pathological grade, and FIGO stage were all risk factors for poor prognosis. A clinical correlation analysis of the relationship between the five autophagy-related lncRNAs and patients' age, pathological grade, and FIGO stage was also per https://orcid.org/0000-0001-7090-1750 formed. Histopathological assessment of the tumor microenvironment showed that the ESTIMATE, immune, and stromal scores in the high-risk group were lower than those in the low-risk group. Principal component analysis and functional annotation were performed to confirm the correlations. To further evaluate the effect of the model constructed on prognosis, samples were divided into training (60%) and validation (40%) groups, regarding the risk status as an independent prognostic risk factor. A prognostic nomogram was constructed using patients' age, pathological grade, FIGO stage, and risk status to estimate the patients' survival rate. C-index and multi-index ROC curves were generated to verify the stability and accuracy of the nomogram. From this analysis, we concluded that the five lncRNAs identified in this study could affect the incidence and development of endometrial cancer by regulating the autophagy process. Therefore, these molecules may have the potential to serve as novel therapeutic targets and biomarkers.

Pompe disease: pathogenesis, molecular genetics and diagnosis

Pompe disease (PD) is a rare autosomal recessive disorder caused by mutations in the GAA gene, localized on chromosome 17 and encoding for acid alpha-1,4-glucosidase (GAA). Currently, more than 560 mutations spread throughout GAA gene have been reported. GAA catalyzes the hydrolysis of α-1,4 and α-1,6-glucosidic bonds of glycogen and its deficiency leads to lysosomal storage of glycogen in several tissues, particularly in muscle. PD is a chronic and progressive pathology usually characterized by limb-girdle muscle weakness and respiratory failure. PD is classified as infantile and childhood/adult forms. PD patients exhibit a multisystemic manifestation that depends on age of onset.

Early diagnosis is essential to prevent or reduce the irreversible organ damage associated with PD progression. Here, we make an overview of PD focusing on pathogenesis, clinical phenotypes, molecular genetics, diagnosis, therapies, autophagy and the role of miRNAs as potential biomarkers for PD.