Predictive SNPs for beta(0)-thalassemia/HbE disease severity

Abstract

beta -Thalassemia/HbE disease has a wide spectrum of clinical phenotypes ranging from asymptomatic to dependent on regular blood transfusions. Ability to predict disease severity is helpful for clinical management and treatment decision making. A thalassemia severity score has been developed from Mediterranean beta -thalassemia patients. However, different ethnic groups may have different allele frequency and linkage disequilibrium structures. Here, Thai beta (0)-thalassemia/HbE disease genome-wild association studies (GWAS) data of 487 patients were analyzed by SNP interaction prioritization algorithm, interacting Loci (iLoci), to find predictive SNPs for disease severity. Three SNPs from two SNP interaction pairs associated with disease severity were identifies. The three-SNP disease severity risk score composed of rs766432 in BCL11A, rs9399137 in HBS1L-MYB and rs72872548 in HBE1 showed more than 85% specificity and 75% accuracy. The three-SNP predictive score was then validated in two independent cohorts of Thai and Malaysian beta (0)-thalassemia/HbE patients with comparable specificity and accuracy. The SNP risk score could be used for prediction of clinical severity for Southeast Asia beta (0)-thalassemia/HbE population.