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Comprehensive analysis of mitochondrial and nuclear DNA variations in patients affected by hemoglobinopathies: A pilot study

The hemoglobin disorders are the most common single gene disorders in the world. Previous studies have suggested that they are deeply geographically structured and a variety of genetic determinants influences different clinical phenotypes between patients inheriting identical β-globin gene mutations...

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Detalles Bibliográficos
Autores principales: Barbanera, Ylenia, Arcioni, Francesco, Lancioni, Hovirag, La Starza, Roberta, Cardinali, Irene, Matteucci, Caterina, Nofrini, Valeria, Roetto, Antonella, Piga, Antonio, Grammatico, Paola, Caniglia, Maurizio, Mecucci, Cristina, Gorello, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581000/
https://www.ncbi.nlm.nih.gov/pubmed/33091040
http://dx.doi.org/10.1371/journal.pone.0240632
Descripción
Sumario:The hemoglobin disorders are the most common single gene disorders in the world. Previous studies have suggested that they are deeply geographically structured and a variety of genetic determinants influences different clinical phenotypes between patients inheriting identical β-globin gene mutations. In order to get new insights into the heterogeneity of hemoglobin disorders, we investigated the molecular variations on nuclear genes (i.e. HBB, HBG2, BCL11A, HBS1L and MYB) and mitochondrial DNA control region. This pilot study was carried out on 53 patients belonging to different continents and molecularly classified in 4 subgroup: β-thalassemia (β(+)/β(+), β(0)/β(0) and β(+)/β(0))(15), sickle cell disease (HbS/HbS)(20), sickle cell/β-thalassemia (HbS/β(+) or HBS/β(0))(10), and non-thalassemic compound heterozygous (HbS/HbC, HbO-Arab/HbC)(8). This comprehensive phylogenetic analysis provided a clear separation between African and European patients either in nuclear or mitochondrial variations. Notably, informing on the phylogeographic structure of affected individuals, this accurate genetic stratification, could help to optimize the diagnostic algorithm for patients with uncertain or unknown origin.