The rs368698783 (G>A) Polymorphism Affecting LYAR Binding to the Aγ-Globin Gene Is Associated with High Fetal Hemoglobin (HbF) in β-Thalassemia Erythroid Precursor Cells Treated with HbF Inducers.
Cristina ZuccatoLucia Carmela CosenzaMatteo ZurloGiulia BreveglieriNicoletta BianchiIlaria LamprontiJessica GasparelloChiara ScapoliMonica BorgattiAlessia FinottiRoberto GambariPublished in: International journal of molecular sciences (2023)
The human homologue of mouse Ly-1 antibody reactive clone protein (LYAR) is a putative novel regulator of γ-globin gene transcription. The LYAR DNA-binding motif (5'-GGTTAT-3') is located within the 5'-UTR of the Aγ-globin gene. The LYAR rs368698783 (G>A) polymorphism is present in β-thalassemia patients and decreases the LYAR binding efficiency to the Aγ-globin gene. The objective of this study was to stratify β-thalassemia patients with respect to the rs368698783 (G>A) polymorphism and to verify whether their erythroid precursor cells (ErPCs) differentially respond in vitro to selected fetal hemoglobin (HbF) inducers. The rs368698783 (G>A) polymorphism was detected by DNA sequencing, hemoglobin production by HPLC, and accumulation of globin mRNAs by RT-qPCR. We found that the LYAR rs368698783 (G>A) polymorphism is associated with high basal and induced production of fetal hemoglobin in β-thalassemia patients. The most striking association was found using rapamycin as an HbF inducer. The results presented here could be considered important not only for basic biomedicine but also in applied translational research for precision medicine in personalized therapy of β-thalassemia. Accordingly, our data suggest that the rs368698783 polymorphism might be considered among the parameters useful to recruit patients with the highest probability of responding to in vivo hydroxyurea (HU) treatment.
Keyphrases
- dna binding
- end stage renal disease
- sickle cell disease
- newly diagnosed
- copy number
- induced apoptosis
- ejection fraction
- genome wide
- transcription factor
- chronic kidney disease
- prognostic factors
- gene expression
- stem cells
- oxidative stress
- cell cycle arrest
- mass spectrometry
- binding protein
- machine learning
- mesenchymal stem cells
- red blood cell
- bone marrow
- cell therapy
- patient reported
- high resolution
- big data
- cell death