Inborn errors of metabolism and the human interactome: a systems medicine approach

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.

The Metabolostasis Network and the Cellular Depository of Aggregation-Prone Metabolites

The vital role of metabolites across all branches of life and their involvement in various disorders have been investigated for decades. Many metabolites are poorly soluble in water or in physiological buffers and tend to form supramolecular aggregates. On the other hand, in the cell, they should be preserved in a pool and be readily available for the execution of biochemical functions. We thus propose that a quality-control network, termed "metabolostasis", has evolved to regulate the storage and retrieval of aggregation-prone metabolites. Such a system should control metabolite concentration, subcellular localization, supramolecular arrangement, and interaction in dynamic environments, thus enabling normal cellular physiology, healthy development, and preventing disease onset. The paradigm-shifting concept of metabolostasis calls for a reevaluation of the traditional view of metabolite storage and dynamics in physiology and pathology and proposes unprecedented directions for therapeutic targets under conditions where metabolostasis is imbalanced.

Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation

Pleiotropy and genetic correlation are widespread features in genome-wide association studies (GWAS), but they are often difficult to interpret at the molecular level. Here, we perform GWAS of 16 metabolites clustered at the intersection of amino acid catabolism, glycolysis, and ketone body metabolism in a subset of UK Biobank. We utilize the well-documented biochemistry jointly impacting these metabolites to analyze pleiotropic effects in the context of their pathways. Among the 213 lead GWAS hits, we find a strong enrichment for genes encoding pathway-relevant enzymes and transporters. We demonstrate that the effect directions of variants acting on biology between metabolite pairs often contrast with those of upstream or downstream variants as well as the polygenic background. Thus, we find that these outlier variants often reflect biology local to the traits. Finally, we explore the implications for interpreting disease GWAS, underscoring the potential of unifying biochemistry with dense metabolomics data to understand the molecular basis of pleiotropy in complex traits and diseases.

Convergent molecular mechanisms underlying cognitive impairment in mucopolysaccharidosis type II

Mucopolysaccharidosis type II (MPS II) is a lysosomal storage disorder caused by pathogenic variants in the iduronate-2-sulfatase gene (IDS), responsible for the degradation of glycosaminoglycans (GAGs) heparan and dermatan sulfate. IDS enzyme deficiency results in the accumulation of GAGs within cells and tissues, including the central nervous system (CNS). The progressive neurological outcome in a representative number of MPSII patients (neuronopathic form) involves cognitive impairment, behavioral difficulties, and regression in developmental milestones. In an attempt to dissect part of the influence of axon guidance instability over the cognitive impairment presentation in MPS II, we used brain expression data, network propagation, and clustering algorithm to prioritize in the human interactome a disease module associated with the MPS II context. We identified new candidate genes and pathways that act in focal adhesion, integrin cell surface, laminin interactions, ECM proteoglycans, cytoskeleton, and phagosome that converge into functional mechanisms involved in early neural circuit formation defects and could indicate clues about cognitive impairment in patients with MPSII. Such molecular changes during neurodevelopment may precede the morphological and clinical evidence, emphasizing the importance of an early diagnosis and directing the development of potential drug leads. Furthermore, our data also support previous hypotheses pointing to shared pathogenic mechanisms in some neurodegenerative diseases.

Current Scenario of Clinical Diagnosis to Identify Inborn Errors of Metabolism with Precision Profiling for Expanded Screening in Infancy in a Resource-limited Setting

Inborn errors of metabolism (IEM) are a diverse collection of abnormalities that cause a variety of morbidities and mortality in children and are classified as uncommon genetic diseases. Early and accurate detection of the condition can save a patient's life. By aiding families as they navigate the experience of having a child with an IEM, healthcare practitioners have the chance to reduce the burden of negative emotional consequences. New therapeutic techniques, such as enzyme replacement and small chemical therapies, organ transplantation, and cellular and gene-based therapies using whole-genome sequencing, have become available in addition to traditional medical intake and cofactor treatments. In the realm of metabolic medicine and metabolomics, the twentyfirst century is an exciting time to be alive. The availability of metabolomics and genomic analysis has led to the identification of a slew of novel diseases. Due to the rarity of individual illnesses, obtaining high-quality data for these treatments in clinical trials and real-world settings has proven difficult. Guidelines produced using standardized techniques have helped enhance treatment delivery and clinical outcomes over time. This article gives a comprehensive description of IEM and how to diagnose it in patients who have developed clinical signs early or late. The appropriate use of standard laboratory outcomes in the preliminary patient assessment is also emphasized that can aid in the ordering of specific laboratory tests to confirm a suspected diagnosis, in addition, to begin treatment as soon as possible in a resource limiting setting where genomic analysis or newborn screening facility is not available.

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.

Glucosylceramide Associated with Gaucher Disease Forms Amyloid-like Twisted Ribbon Fibrils That Induce α-Synuclein Aggregation

A major risk factor for Gaucher's disease is loss of function mutations in the GBA1 gene that encodes lysosomal β-glucocerebrosidase, resulting in accumulation of glucosylceramide (GlcCer), a key lysosomal sphingolipid. GBA1 mutations also enhance the risk for Parkinson's disease, whose hallmark is the aggregation of α-synuclein (αSyn). However, the role of accumulated GlcCer in αSyn aggregation is not completely understood. Using various biophysical assays, we demonstrate that GlcCer self-assembles to form amyloid-like fibrillar aggregates in vitro. The GlcCer assemblies are stable in aqueous media of different pH and exhibit a twisted ribbon-like structure. Near lysosomal pH GlcCer aggregates induced αSyn aggregation and stabilized its nascent oligomers. We found that several bona fide inhibitors of proteinaceous amyloids effectively inhibited aggregation of GlcCer. This study contributes to the growing evidence of cross-talk between proteinaceous amyloids and amyloid-like aggregates of metabolites accumulated in diseases and suggests these aggregates as therapeutic targets.

IRS-2/Akt/GSK-3β/Nrf2 Pathway Contributes to the Protective Effects of Chikusetsu Saponin IVa against Lipotoxicity

Chronic hyperlipidemia leads to pancreatic β-cell apoptosis and dysfunction through inducing oxidative stress. Chikusetsu saponin IVa (CHS) showed antioxidant and antidiabetic properties in our previous studies; however, its protective effects against lipotoxicity-induced β-cell oxidative stress and dysfunction are not clear. This study was designed to investigate the effects of CHS against lipotoxicity-induced β-cell injuries and its possible mechanism involved. High-fat (HF) diet and a low dose of streptozotocin- (STZ-) induced type 2 diabetes mellitus (T2DM) model in vivo and βTC3 cells subjected to 0.5 mM palmitate (PA) to imitate the lipotoxic model in vitro were performed. Pancreatic functions, ROS, and antioxidant protein measurements were performed to evaluate the effects of CHS on cell injuries. Protein expression levels were measured by Western blotting. Furthermore, siRNA-targeted Nrf2, PI3K/Akt inhibitor (LY294002), or GSK-3β inhibitor (LiCl) was used to investigate the crosstalk relationships between proteins. As the results showed, CHS treatment inhibited apoptosis, promoted insulin release, and reduced oxidative stress. CHS treatment significantly increased the expression of Nrf2 in the cytoplasm and nuclear protein. The antioxidative and benefit effects of CHS were inhibited by siNrf2. The phosphorylation of IRS-2, PI3K, Akt, and GSK-3β was markedly increased by CHS which were inhibited by PA. In addition, inhibition of PI3K/Akt or GSK-3β with specific inhibitors dramatically abrogated the protective effects of CHS, revealing that the IRS-2/Akt/GSK-3β signaling axis was involved in the protective effects of CHS. These results demonstrate that CHS protected βTC3 cells against PA-induced oxidative stress and cell dysfunction through Nrf2 by the IRS-2/Akt/GSK-3β-mediated pathway.

Regulation of H2O2-induced cells injury through Nrf2 signaling pathway: An introduction of a novel cysteic acid-modified peptide

A novel peptide (Cya-Phe-Leu-Ala-Pro, SCP) was formulated through non-protein amino acid-cysteic acid (Cya) modification of collagen peptide (Phe-Leu-Ala-Pro, CP) from Acaudina molpadioides. Introduction of this Cya showed remarkable improvement in the scavenging activities of OH·. SCP exhibited stronger effects than CP in preventing H₂O₂-induced oxidative damage due to lower levels of ROS and MDA, and higher activities of antioxidant enzymes, such as SOD, GSH-Px, HO-1, and NQO1. It was speculated that SCP could significantly increase the expression level of Nrf2 compared to CP, thereby activating the expression of downstream ARE genes. The expression levels of p38 in the upstream pathway to regulate Nrf2 content were significantly higher in both the CP and SCP-treated groups, while a higher level of JNK was observed only in the SCP-treated groups. The present study provided insights towards the application of cysteic acid modified peptide in protecting cell from oxidative damage through the JNK/Nrf2 pathway.

Network Analysis Reveals Proteins Associated with Aortic Dilatation in Mucopolysaccharidoses

Mucopolysaccharidoses are caused by a deficiency of enzymes involved in the degradation of glycosaminoglycans. Heart diseases are a significant cause of morbidity and mortality in MPS patients, even in conditions in which enzyme replacement therapy is available. In this sense, cardiovascular manifestations, such as heart hypertrophy, cardiac function reduction, increased left ventricular chamber, and aortic dilatation, are among the most frequent. However, the downstream events which influence the heart dilatation process are unclear. Here, we employed systems biology tools together with transcriptomic data to investigate new elements that may be involved in aortic dilatation in Mucopolysaccharidoses syndrome. We identified candidate genes involved in biological processes related to inflammatory responses, deposition of collagen, and lipid accumulation in the cardiovascular system that may be involved in aortic dilatation in the Mucopolysaccharidoses I and VII. Furthermore, we investigated the molecular mechanisms of losartan treatment in Mucopolysaccharidoses I mice to underscore how this drug acts to prevent aortic dilation. Our data indicate that the association between the TGF-b signaling pathway, Fos, and Col1a1 proteins can play an essential role in aortic dilation's pathophysiology and its subsequent improvement by losartan treatment.

Occurrence of Inborn Errors of Metabolism in Newborns, Diagnosis and Prophylaxis

Inborn errors of metabolism (IEM) are a heterogeneous group of rare genetic disorders that are generally transmitted as autosomal or X-linked recessive disorders. These defects arise due to mutations associated with specific gene(s), especially the ones associated with key metabolic enzymes. These enzymes or their product(s) are involved in various metabolic pathways, leading to the accumulation of intermediary metabolite(s), reflecting their toxic effects upon mutations. The diagnosis of these metabolic disorders is based on the biochemical analysis of the clinical manifestations produced and their molecular mechanism. Therefore, it is imperative to devise diagnostic tests with high sensitivity and specificity for early detection of IEM. Recent advances in biochemical and polymerase chain reaction-based genetic analysis along with pedigree and prenatal diagnosis can be life-saving in nature. The latest development in exome sequencing for rapid diagnosis and enzyme replacement therapy would facilitate the successful treatment of these metabolic disorders in the future. However, the longterm clinical implications of these genetic manipulations is still a matter of debate among intellectuals and requires further research.

Identification of breast cancer risk modules via an integrated strategy

Breast cancer is one of the most common malignant cancers among females worldwide. This complex disease is not caused by a single gene, but resulted from multi-gene interactions, which could be represented by biological networks. Network modules are composed of genes with significant similarities in terms of expression, function and disease association. Therefore, the identification of disease risk modules could contribute to understanding the molecular mechanisms underlying breast cancer. In this paper, an integrated disease risk module identification strategy was proposed according to a multi-objective programming model for two similarity criteria as well as significance of permutation tests in Markov random field module score, function consistency score and Pearson correlation coefficient difference score. Three breast cancer risk modules were identified from a breast cancer-related interaction network. Genes in these risk modules were confirmed to play critical roles in breast cancer by literature review. These risk modules were enriched in breast cancer-related pathways or functions and could distinguish between breast tumor and normal samples with high accuracy for not only the microarray dataset used for breast cancer risk module identification, but also another two independent datasets. Our integrated strategy could be extended to other complex diseases to identify their risk modules and reveal their pathogenesis.

Translational Metabolism: A multidisciplinary approach towards precision diagnosis of inborn errors of metabolism in the omics era

The laboratory diagnosis of inborn errors of metabolism has been revolutionized in recent years, thanks to the amazing developments in the field of DNA sequencing including whole exome and whole genome sequencing (WES and WGS). Interpretation of the results coming from WES and/or WGS analysis is definitely not trivial especially since the biological relevance of many of the variants identified by WES and/or WGS, have not been tested experimentally and prediction programs like POLYPHEN-2 and SIFT are far from perfect. Correct interpretation of WES and/or WGS results can only be achieved by performing functional studies at multiple levels (different metabolomics platforms, enzymology, in vitro and in vivo flux analysis), often requires studies in model organisms like zebra fish, Caenorhabditis elegans, Saccharomyces cerevisiae, mutant mice and others, and also requires the input of many different disciplines to make this Translational Metabolism approach effective.

Metabolomics in the clinic: A review of the shared and unique features of untargeted metabolomics for clinical research and clinical testing

Metabolomics is the untargeted measurement of the metabolome, which is composed of the complement of small molecules detected in a biological sample. As such, metabolomic analysis produces a global biochemical phenotype. It is a technology that has been utilized in the research setting for over a decade. The metabolome is directly linked to and is influenced by genetics, epigenetics, environmental factors, and the microbiome-all of which affect health. Metabolomics can be applied to human clinical diagnostics and to other fields such as veterinary medicine, nutrition, exercise, physiology, agriculture/plant biochemistry, and toxicology. Applications of metabolomics in clinical testing are emerging, but several aspects of its use as a clinical test differ from applications focused on research or biomarker discovery and need to be considered for metabolomics clinical test data to have optimum impact, be meaningful, and be used responsibly. In this review, we deconstruct aspects and challenges of metabolomics for clinical testing by illustrating the significance of test design, accurate and precise data acquisition, quality control, data processing, n-of-1 comparison to a reference population, and biochemical pathway analysis. We describe how metabolomics technology is integral to defining individual biochemical phenotypes, elaborates on human health and disease, and fits within the precision medicine landscape. Finally, we conclude by outlining some future steps needed to bring metabolomics into the clinical space and to be recognized by the broader medical and regulatory fields.