Identification of Clinical Variants beyond the Exome in Inborn Errors of Metabolism
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 new...
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| Published in | International journal of molecular sciences Vol. 23; no. 21; p. 12850 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
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MDPI AG
01.11.2022
MDPI |
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| Online Access | Get full text |
| ISSN | 1422-0067 1661-6596 1422-0067 |
| DOI | 10.3390/ijms232112850 |
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| 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 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. |
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| AbstractList | 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. 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. 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.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. |
| Author | Quijada-Fraile, Pilar Pérez, Belén Correcher, Patricia Couce, María L. Soriano-Sexto, Alejandro Alcaide, Patricia Martín-Hernández, Elena Leal, Fátima Ugarte, Magdalena Peña-Quintana, Luis Rodríguez-Pombo, Pilar Navarrete, Rosa Castejón-Fernández, Natalia Yahyaoui, Raquel Gallego, Diana |
| AuthorAffiliation | 6 Nutrition and Metabolophaties Unit, Hospital Universitario La Fe, 46026 Valencia, Spain 3 Unidad de Enfermedades Mitocondriales-Metabólicas Hereditarias, Servicio de Pediatría, Centro de Referencia Nacional (CSUR) y Europeo (MetabERN) para Enfermedades Metabólicas Hereditarias, Hospital Universitario 12 de Octubre, 28041 Madrid, Spain 4 Pediatric Gastroenterology, Hepatology and Nutrition Unit, Complejo Hospitalario Universitario Insular Materno-Infantil (CHUIMI), Universidad de Las Palmas de Gran Canaria, Asociación Canaria para La Investigación Pediátrica, Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) ISCIII, 35016 Gran Canaria, Spain 1 Centro de Diagnóstico de Enfermedades Moleculares, Centro de Biología Molecular, Departamento de Biología Molecular, Universidad Autónoma de Madrid, Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), IdiPAZ, 28049 Madrid, Spain 2 Unit for the Diagnosis and Treatment of Conge |
| AuthorAffiliation_xml | – name: 4 Pediatric Gastroenterology, Hepatology and Nutrition Unit, Complejo Hospitalario Universitario Insular Materno-Infantil (CHUIMI), Universidad de Las Palmas de Gran Canaria, Asociación Canaria para La Investigación Pediátrica, Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) ISCIII, 35016 Gran Canaria, Spain – name: 6 Nutrition and Metabolophaties Unit, Hospital Universitario La Fe, 46026 Valencia, Spain – name: 5 Laboratory of Metabolic Disorders and Newborn Screening, Institute of Biomedical Research in Málaga (IBIMA-Plafatorma BIONAND), IBIMA-RARE, Málaga Regional University Hospital, 29010 Málaga, Spain – name: 2 Unit for the Diagnosis and Treatment of Congenital Metabolic Diseases, Clinical University Hospital of Santiago de Compostela, Health Research Institute of Santiago de Compostela, University of Santiago de Compostela, CIBERER, MetabERN, 15706 Santiago de Compostela, Spain – name: 1 Centro de Diagnóstico de Enfermedades Moleculares, Centro de Biología Molecular, Departamento de Biología Molecular, Universidad Autónoma de Madrid, Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), IdiPAZ, 28049 Madrid, Spain – name: 3 Unidad de Enfermedades Mitocondriales-Metabólicas Hereditarias, Servicio de Pediatría, Centro de Referencia Nacional (CSUR) y Europeo (MetabERN) para Enfermedades Metabólicas Hereditarias, Hospital Universitario 12 de Octubre, 28041 Madrid, Spain |
| Author_xml | – sequence: 1 givenname: Alejandro orcidid: 0000-0001-8294-7166 surname: Soriano-Sexto fullname: Soriano-Sexto, Alejandro – sequence: 2 givenname: Diana orcidid: 0000-0002-3866-7316 surname: Gallego fullname: Gallego, Diana – sequence: 3 givenname: Fátima surname: Leal fullname: Leal, Fátima – sequence: 4 givenname: Natalia surname: Castejón-Fernández fullname: Castejón-Fernández, Natalia – sequence: 5 givenname: Rosa surname: Navarrete fullname: Navarrete, Rosa – sequence: 6 givenname: Patricia orcidid: 0000-0001-9156-2049 surname: Alcaide fullname: Alcaide, Patricia – sequence: 7 givenname: María L. orcidid: 0000-0003-4861-9905 surname: Couce fullname: Couce, María L. – sequence: 8 givenname: Elena surname: Martín-Hernández fullname: Martín-Hernández, Elena – sequence: 9 givenname: Pilar orcidid: 0000-0003-1026-4854 surname: Quijada-Fraile fullname: Quijada-Fraile, Pilar – sequence: 10 givenname: Luis orcidid: 0000-0001-6052-5894 surname: Peña-Quintana fullname: Peña-Quintana, Luis – sequence: 11 givenname: Raquel orcidid: 0000-0001-6789-1563 surname: Yahyaoui fullname: Yahyaoui, Raquel – sequence: 12 givenname: Patricia orcidid: 0000-0002-9704-9534 surname: Correcher fullname: Correcher, Patricia – sequence: 13 givenname: Magdalena surname: Ugarte fullname: Ugarte, Magdalena – sequence: 14 givenname: Pilar orcidid: 0000-0001-9315-5906 surname: Rodríguez-Pombo fullname: Rodríguez-Pombo, Pilar – sequence: 15 givenname: Belén orcidid: 0000-0002-3190-1958 surname: Pérez fullname: Pérez, Belén |
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| Title | Identification of Clinical Variants beyond the Exome in Inborn Errors of Metabolism |
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