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Molecular Research on Inherited Metabolic Disorders 2.0

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pathology, Diagnostics, and Therapeutics".

Deadline for manuscript submissions: closed (28 February 2024) | Viewed by 10926

Special Issue Editors


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Guest Editor
Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy
Interests: inherited metabolic disorders; metabolomics; newborn screening; proteomics; protein-protein interaction
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Guest Editor
Proteomics Platform 3P5-Necker, Université Paris Descartes - Structure Fédérative de Recherche Necker, INSERM US24/CNRS UMS3633, 75014 Paris, France
Interests: rare genetic disease; proteomics; glycoproteomics; multi-omics; system biology; extracellular vesicles
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Rapid advances have been made in the prediction, detection, understanding, and monitoring of inherited disorders in humans using proteomic and metabolomic technologies. These disorders are genetic conditions that result in metabolism problems. Most people with inherited disorders have a defective gene that results in an enzyme deficiency and/or gains of function. There are hundreds of different genetic metabolic disorders, and their symptoms, treatments, and prognoses vary widely. Examples of these disorders include aminoacidopathies, defects of the oxidation of fatty acids, organic acidemias, lysosomal storage disease, and disorders of glycosylation.

The rarity of these conditions places a considerable burden on the individuals affected and contributes to significant challenges in the medical care of these patients. It is clear that treatments applied as early as possible could greatly improve outcomes for patients.

Molecular research and in particular proteomics and metabolomics offers great promise in this field. On one hand, they led to the discovery of new, biologically and clinically relevant biomarkers for inherited metabolic disorders, for both diagnosis and prognosis. On the other hand, they contribute new knowledge in terms of the molecular mechanisms of inherited metabolic disorders. Furthermore, the combined proteo-metabolomic approaches are developing rapidly, and are particularly relevant in understanding metabolic diseases.

The Special Issue will be devoted to molecular research in Inherited Disorders. It will contain up-to-date review articles, plus original research, concerning any aspect of molecular mechanism, diagnosis and treatment of Inherited Disorders to provide a state-of-the-art overview of this fast-moving area.

Prof. Dr. Margherita Ruoppolo
Dr. Ida Chiara Guerrera
Guest Editors

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Keywords

  • differential proteomics
  • fluxomics
  • glycoproteomics
  • human disease model
  • inherited disorders
  • mass spectrometry
  • multi-omics
  • protein–protein interactions
  • NMR
  • targeted metabolomics
  • untargeted metabolomics

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Published Papers (5 papers)

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12 pages, 3046 KiB  
Article
A Novel Mutation in the INSR Gene Causes Severe Insulin Resistance and Rabson–Mendenhall Syndrome in a Paraguayan Patient
by Maria Natalia Rojas Velazquez, Fabiola Blanco, Ana Ayala-Lugo, Lady Franco, Valerie Jolly, Denisse Di Tore, Idoia Martínez de Lapiscina, Marco Janner, Christa E. Flück and Amit V. Pandey
Int. J. Mol. Sci. 2024, 25(6), 3143; https://doi.org/10.3390/ijms25063143 - 8 Mar 2024
Cited by 1 | Viewed by 2121
Abstract
Rabson–Mendenhall syndrome (RMS) is a rare autosomal recessive disorder characterized by severe insulin resistance, resulting in early-onset diabetes mellitus. We report the first case of RMS in a Paraguayan patient. The patient is a 6-year-old girl who presented with hypertrichosis, acanthosis nigricans, nephrocalcinosis, [...] Read more.
Rabson–Mendenhall syndrome (RMS) is a rare autosomal recessive disorder characterized by severe insulin resistance, resulting in early-onset diabetes mellitus. We report the first case of RMS in a Paraguayan patient. The patient is a 6-year-old girl who presented with hypertrichosis, acanthosis nigricans, nephrocalcinosis, and elevated levels of glucose and insulin that served as diagnostic indicators for RMS. Genetic testing by next-generation sequencing (NGS) revealed two pathogenic variants in exons 2 and 19 of the INSR gene: c.332G>T (p.Gly111Val) and c.3485C>T (p.Ala1162Val), in combined heterozygosis. The novel INSR c. 332G>T variant leads to the substitution of glycine to valine at position 111 in the protein, and multiple in silico software programs predicted it as pathogenic. The c.3485C>T variant leads to the substitution of alanine to valine at position 1162 in the protein previously described for insulin resistance and RMS. The management of RMS is particularly challenging in children, and the use of metformin is often limited by its side effects. The patient was managed with nutritional measures due to the early age of onset. This report expands the knowledge of RMS to the Paraguayan population and adds a novel pathogenic variant to the existing literature. Full article
(This article belongs to the Special Issue Molecular Research on Inherited Metabolic Disorders 2.0)
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21 pages, 7016 KiB  
Article
Metabolic Rewiring and Altered Glial Differentiation in an iPSC-Derived Astrocyte Model Derived from a Nonketotic Hyperglycinemia Patient
by Laura Arribas-Carreira, Margarita Castro, Fernando García, Rosa Navarrete, Irene Bravo-Alonso, Francisco Zafra, Magdalena Ugarte, Eva Richard, Belén Pérez and Pilar Rodríguez-Pombo
Int. J. Mol. Sci. 2024, 25(5), 2814; https://doi.org/10.3390/ijms25052814 - 28 Feb 2024
Viewed by 1812
Abstract
The pathophysiology of nonketotic hyperglycinemia (NKH), a rare neuro-metabolic disorder associated with severe brain malformations and life-threatening neurological manifestations, remains incompletely understood. Therefore, a valid human neural model is essential. We aimed to investigate the impact of GLDC gene variants, which cause NKH, [...] Read more.
The pathophysiology of nonketotic hyperglycinemia (NKH), a rare neuro-metabolic disorder associated with severe brain malformations and life-threatening neurological manifestations, remains incompletely understood. Therefore, a valid human neural model is essential. We aimed to investigate the impact of GLDC gene variants, which cause NKH, on cellular fitness during the differentiation process of human induced pluripotent stem cells (iPSCs) into iPSC-derived astrocytes and to identify sustainable mechanisms capable of overcoming GLDC deficiency. We developed the GLDC27-FiPS4F-1 line and performed metabolomic, mRNA abundance, and protein analyses. This study showed that although GLDC27-FiPS4F-1 maintained the parental genetic profile, it underwent a metabolic switch to an altered serine–glycine–one-carbon metabolism with a coordinated cell growth and cell cycle proliferation response. We then differentiated the iPSCs into neural progenitor cells (NPCs) and astrocyte-lineage cells. Our analysis showed that GLDC-deficient NPCs had shifted towards a more heterogeneous astrocyte lineage with increased expression of the radial glial markers GFAP and GLAST and the neuronal markers MAP2 and NeuN. In addition, we detected changes in other genes related to serine and glycine metabolism and transport, all consistent with the need to maintain glycine at physiological levels. These findings improve our understanding of the pathology of nonketotic hyperglycinemia and offer new perspectives for therapeutic options. Full article
(This article belongs to the Special Issue Molecular Research on Inherited Metabolic Disorders 2.0)
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10 pages, 597 KiB  
Article
Nitisinone Treatment Affects Biomarkers of Bone and Cartilage Remodelling in Alkaptonuria Patients
by Federica Genovese, Peder Frederiksen, Anne-Christine Bay-Jensen, Morten A. Karsdal, Anna M. Milan, Birgitta Olsson, Mattias Rudebeck, James A. Gallagher and Lakshminarayan R. Ranganath
Int. J. Mol. Sci. 2023, 24(13), 10996; https://doi.org/10.3390/ijms241310996 - 1 Jul 2023
Cited by 3 | Viewed by 1373
Abstract
Nitisinone has been approved for treatment of alkaptonuria (AKU). Non-invasive biomarkers of joint tissue remodelling could aid in understanding the molecular changes in AKU pathogenesis and how these can be affected by treatment. Serological and urinary biomarkers of type I collagen and II [...] Read more.
Nitisinone has been approved for treatment of alkaptonuria (AKU). Non-invasive biomarkers of joint tissue remodelling could aid in understanding the molecular changes in AKU pathogenesis and how these can be affected by treatment. Serological and urinary biomarkers of type I collagen and II collagen in AKU were investigated in patients enrolled in the randomized SONIA 2 (NCT01916382) clinical study at baseline and yearly until the end of the study (Year 4). The trajectories of the biomarkers over time were observed. After treatment with nitisinone, the biomarkers of type I collagen remodelling increased at Year 1 (19% and 40% increase in CTX-I and PRO-C1, respectively), which was potentially reflected in the higher degree of mobility seen following treatment. The biomarkers of type II collagen remodelling decreased over time in the nitisinone group: C2M showed a 9.7% decline at Year 1, and levels then remained stable over the following visits; CTX-II showed a 26% decline at Year 3 and 4 in the nitisinone-treated patients. Nitisinone treatment induced changes in biomarkers of bone and cartilage remodelling. These biomarkers can aid patient management and deepen our knowledge of the molecular mechanisms of this rare disease. Full article
(This article belongs to the Special Issue Molecular Research on Inherited Metabolic Disorders 2.0)
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15 pages, 2002 KiB  
Article
Comparison between Sickle Cell Disease Patients and Healthy Donors: Untargeted Lipidomic Study of Erythrocytes
by Husam B. R. Alabed, Paolo Gorello, Roberto Maria Pellegrino, Hovirag Lancioni, Roberta La Starza, Anna Aurora Taddei, Lorena Urbanelli, Sandra Buratta, Anair Graciela Lema Fernandez, Caterina Matteucci, Maurizio Caniglia, Francesco Arcioni, Cristina Mecucci and Carla Emiliani
Int. J. Mol. Sci. 2023, 24(3), 2529; https://doi.org/10.3390/ijms24032529 - 28 Jan 2023
Cited by 3 | Viewed by 2375
Abstract
Sickle cell disease (SCD) is one of the most common severe monogenic disorders in the world caused by a mutation on HBB gene and characterized by hemoglobin polymerization, erythrocyte rigidity, vaso-occlusion, chronic anemia, hemolysis, and vasculopathy. Recently, the scientific community has focused on [...] Read more.
Sickle cell disease (SCD) is one of the most common severe monogenic disorders in the world caused by a mutation on HBB gene and characterized by hemoglobin polymerization, erythrocyte rigidity, vaso-occlusion, chronic anemia, hemolysis, and vasculopathy. Recently, the scientific community has focused on the multiple genetic and clinical profiles of SCD. However, the lipid composition of sickle cells has received little attention in the literature. According to recent studies, changes in the lipid profile are strongly linked to several disorders. Therefore, the aim of this study is to dig deeper into lipidomic analysis of erythrocytes in order to highlight any variations between healthy and patient subjects. 241 lipid molecular species divided into 17 classes have been annotated and quantified. Lipidomic profiling of SCD patients showed that over 24% of total lipids were altered most of which are phospholipids. In-depth study of significant changes in lipid metabolism can give an indication of the enzymes and genes involved. In a systems biology scenario, these variations can be useful to improve the understanding of the biochemical basis of SCD and to try to make a score system that could be predictive for the severity of clinical manifestations. Full article
(This article belongs to the Special Issue Molecular Research on Inherited Metabolic Disorders 2.0)
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15 pages, 1908 KiB  
Article
Identification of Clinical Variants beyond the Exome in Inborn Errors of Metabolism
by Alejandro Soriano-Sexto, Diana Gallego, Fátima Leal, Natalia Castejón-Fernández, Rosa Navarrete, Patricia Alcaide, María L. Couce, Elena Martín-Hernández, Pilar Quijada-Fraile, Luis Peña-Quintana, Raquel Yahyaoui, Patricia Correcher, Magdalena Ugarte, Pilar Rodríguez-Pombo and Belén Pérez
Int. J. Mol. Sci. 2022, 23(21), 12850; https://doi.org/10.3390/ijms232112850 - 25 Oct 2022
Cited by 5 | Viewed by 2543
Abstract
Inborn errors of metabolism (IEM) constitute a huge group of rare diseases affecting 1 in every 1000 newborns. Next-generation sequencing has transformed the diagnosis of IEM, leading to its proposed use as a second-tier technology for confirming cases detected by clinical/biochemical studies or [...] Read more.
Inborn errors of metabolism (IEM) constitute a huge group of rare diseases affecting 1 in every 1000 newborns. Next-generation sequencing has transformed the diagnosis of IEM, leading to its proposed use as a second-tier technology for confirming cases detected by clinical/biochemical studies or newborn screening. The diagnosis rate is, however, still not 100%. This paper reports the use of a personalized multi-omics (metabolomic, genomic and transcriptomic) pipeline plus functional genomics to aid in the genetic diagnosis of six unsolved cases, with a clinical and/or biochemical diagnosis of galactosemia, mucopolysaccharidosis type I (MPS I), maple syrup urine disease (MSUD), hyperphenylalaninemia (HPA), citrullinemia, or urea cycle deficiency. Eight novel variants in six genes were identified: six (four of them deep intronic) located in GALE, IDUA, PTS, ASS1 and OTC, all affecting the splicing process, and two located in the promoters of IDUA and PTS, thus affecting these genes’ expression. All the new variants were subjected to functional analysis to verify their pathogenic effects. This work underscores how the combination of different omics technologies and functional analysis can solve elusive cases in clinical practice. Full article
(This article belongs to the Special Issue Molecular Research on Inherited Metabolic Disorders 2.0)
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