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Genetic Modifiers at the Crossroads of Personalised Medicine for Haemoglobinopathies
Haemoglobinopathies are common monogenic disorders with diverse clinical manifestations, partly attributed to the influence of modifier genes. Recent years have seen enormous growth in the amount of genetic data, instigating the need for ranking methods to identify candidate genes with strong modify...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6912721/ https://www.ncbi.nlm.nih.gov/pubmed/31717530 http://dx.doi.org/10.3390/jcm8111927 |
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author | Stephanou, Coralea Tamana, Stella Minaidou, Anna Papasavva, Panayiota Kleanthous, Marina Kountouris, Petros |
author_facet | Stephanou, Coralea Tamana, Stella Minaidou, Anna Papasavva, Panayiota Kleanthous, Marina Kountouris, Petros |
author_sort | Stephanou, Coralea |
collection | PubMed |
description | Haemoglobinopathies are common monogenic disorders with diverse clinical manifestations, partly attributed to the influence of modifier genes. Recent years have seen enormous growth in the amount of genetic data, instigating the need for ranking methods to identify candidate genes with strong modifying effects. Here, we present the first evidence-based gene ranking metric (IthaScore) for haemoglobinopathy-specific phenotypes by utilising curated data in the IthaGenes database. IthaScore successfully reflects current knowledge for well-established disease modifiers, while it can be dynamically updated with emerging evidence. Protein–protein interaction (PPI) network analysis and functional enrichment analysis were employed to identify new potential disease modifiers and to evaluate the biological profiles of selected phenotypes. The most relevant gene ontology (GO) and pathway gene annotations for (a) haemoglobin (Hb) F levels/Hb F response to hydroxyurea included urea cycle, arginine metabolism and vascular endothelial growth factor receptor (VEGFR) signalling, (b) response to iron chelators included xenobiotic metabolism and glucuronidation, and (c) stroke included cytokine signalling and inflammatory reactions. Our findings demonstrate the capacity of IthaGenes, together with dynamic gene ranking, to expand knowledge on the genetic and molecular basis of phenotypic variation in haemoglobinopathies and to identify additional candidate genes to potentially inform and improve diagnosis, prognosis and therapeutic management. |
format | Online Article Text |
id | pubmed-6912721 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-69127212020-01-02 Genetic Modifiers at the Crossroads of Personalised Medicine for Haemoglobinopathies Stephanou, Coralea Tamana, Stella Minaidou, Anna Papasavva, Panayiota Kleanthous, Marina Kountouris, Petros J Clin Med Article Haemoglobinopathies are common monogenic disorders with diverse clinical manifestations, partly attributed to the influence of modifier genes. Recent years have seen enormous growth in the amount of genetic data, instigating the need for ranking methods to identify candidate genes with strong modifying effects. Here, we present the first evidence-based gene ranking metric (IthaScore) for haemoglobinopathy-specific phenotypes by utilising curated data in the IthaGenes database. IthaScore successfully reflects current knowledge for well-established disease modifiers, while it can be dynamically updated with emerging evidence. Protein–protein interaction (PPI) network analysis and functional enrichment analysis were employed to identify new potential disease modifiers and to evaluate the biological profiles of selected phenotypes. The most relevant gene ontology (GO) and pathway gene annotations for (a) haemoglobin (Hb) F levels/Hb F response to hydroxyurea included urea cycle, arginine metabolism and vascular endothelial growth factor receptor (VEGFR) signalling, (b) response to iron chelators included xenobiotic metabolism and glucuronidation, and (c) stroke included cytokine signalling and inflammatory reactions. Our findings demonstrate the capacity of IthaGenes, together with dynamic gene ranking, to expand knowledge on the genetic and molecular basis of phenotypic variation in haemoglobinopathies and to identify additional candidate genes to potentially inform and improve diagnosis, prognosis and therapeutic management. MDPI 2019-11-09 /pmc/articles/PMC6912721/ /pubmed/31717530 http://dx.doi.org/10.3390/jcm8111927 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Stephanou, Coralea Tamana, Stella Minaidou, Anna Papasavva, Panayiota Kleanthous, Marina Kountouris, Petros Genetic Modifiers at the Crossroads of Personalised Medicine for Haemoglobinopathies |
title | Genetic Modifiers at the Crossroads of Personalised Medicine for Haemoglobinopathies |
title_full | Genetic Modifiers at the Crossroads of Personalised Medicine for Haemoglobinopathies |
title_fullStr | Genetic Modifiers at the Crossroads of Personalised Medicine for Haemoglobinopathies |
title_full_unstemmed | Genetic Modifiers at the Crossroads of Personalised Medicine for Haemoglobinopathies |
title_short | Genetic Modifiers at the Crossroads of Personalised Medicine for Haemoglobinopathies |
title_sort | genetic modifiers at the crossroads of personalised medicine for haemoglobinopathies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6912721/ https://www.ncbi.nlm.nih.gov/pubmed/31717530 http://dx.doi.org/10.3390/jcm8111927 |
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