Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literature
Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
15 authors at 6 institutions in 1 country.
Alejandro Soriano-SextoCentro 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.ORCID 0000-0001-8294-7166
Diana GallegoCentro 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.ORCID 0000-0002-3866-7316
Fátima LealCentro 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.
Natalia Castejón-FernándezCentro 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.
Rosa NavarreteCentro 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.
Patricia AlcaideCentro 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.ORCID 0000-0001-9156-2049
María L CouceUnit 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.ORCID 0000-0003-4861-9905
Elena Martín-HernándezUnidad 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.
Pilar Quijada-FraileUnidad 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.ORCID 0000-0003-1026-4854
Luis Peña-QuintanaPediatric 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.ORCID 0000-0001-6052-5894
Raquel YahyaouiLaboratory of Metabolic Disorders and Newborn Screening, Institute of Biomedical Research in Málaga (IBIMA-Plafatorma BIONAND), IBIMA-RARE, Málaga Regional University Hospital, 29010 Málaga, Spain.ORCID 0000-0001-6789-1563
Patricia CorrecherNutrition and Metabolophaties Unit, Hospital Universitario La Fe, 46026 Valencia, Spain.ORCID 0000-0002-9704-9534
Magdalena UgarteCentro 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.
Pilar Rodríguez-PomboCentro 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.ORCID 0000-0001-9315-5906
Belén PérezCentro 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.ORCID 0000-0002-3190-1958
Centre for Biomedical Network Research on Rare Diseases · ESHospital Universitario 12 De Octubre · ESHospital Universitari i Politècnic La Fe · ESInstituto de Investigación Biomédica de Málaga · ESUniversidad de Las Palmas de Gran Canaria · ESUniversidade de Santiago de Compostela · ES
Funding
Consejería de Educación, Juventud y Deporte B2017/BMD3721Instituto de Salud Carlos III (ISCIII), the European Regional Development Fund PI19/01155NIMHD NIH HHS L60 MD003721
6 · The paper itself
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
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Identification of Clinical Variants beyond the Exome in Inborn Errors of Metabolism. · full record | OpenQuestion