Phenotypic prediction in beta-thalassemia

The Prevalence of HBB Mutations among the Transfusion-Dependent and Non Transfusion-Dependent Hb E/β-Thalassemia Children in a Tertiary Center of West Bengal, India

Hb E (HBB: c.79G>A)/β-thalassemia (Hb E/β-thal) is responsible for nearly half of all the different kinds of severe β-thal. This disorder is characterized by a wide range of clinical variability ranging from mild, asymptomatic non transfusion-dependent thalassemia (NTDT) to severe transfusion-dependent thalassemia (TDT). The aim of the present study was to determine the prevalence of different β-globin gene (HBB) mutations in Hb E/β-thal subjects and their potential role in transfusion dependence. One hundred and ten consecutive children with Hb E/β-thal attending the Pediatric Department of Burdwan Medical College, Burdwan, West Bengal, India were enrolled. Based on hemoglobin (Hb) electrophoresis or high-performance liquid chromatography (HPLC), patients were recruited and later β-globin gene sequencing was done to find out the prevalence of different HBB mutations. Transfusion-dependent thalassemia was seen in 42 children (38.2%), while NTDT was seen in 68 children (61.8%). A total of 10 different β-globin mutant alleles were characterized. The most frequent mutation on the β-globin gene was IVS-I-5 (G>C) (HBB: c0.92+5G>C) in both groups. The β-globin gene mutations alone cannot determine transfusion dependence among the Hb E/β-thal patients.

Molecular analysis of β-thalassemia patients: first identification of mutations HBB:c.93-2A>G and HBB:c.114G>A in Brazil

The various clinical phenotypes in β-thalassemias have stimulated the study of genetic factors that could modify the manifestations of these diseases. We examined 21 patients with β-thalassemia (β-thal) in order to identify some genetic modifying factors: β-thalassemia mutations, HBG2:g.-158C>T polymorphism, α-globin gene deletions and (AT)xNz(AT)y motif within the hypersensitive site 2-locus control region (HS2-LCR). In the 42 alleles analyzed, the most frequent mutations observed were HBB:c.92+6T>C (30.9%), HBB:c.118C>T (16.7%), HBB:c.93-21G>A (11.9%) and HBB:c.92+1G>A (4.8%); this finding is in accordance with previous data of the Brazilian population. The other genetic factors analyzed showed no relation with the severity of the disease. For the first time in Brazil, we report HBB:c.93-2A>G and HBB:c.114G>A mutations on the β-globin gene, both in a heterozygous state. This is also the first study to analyze the HS2-LCR in β-thalassemic individuals in the Brazilian population.

Disease-associated mutations that alter the RNA structural ensemble

Genome-wide association studies (GWAS) often identify disease-associated mutations in intergenic and non-coding regions of the genome. Given the high percentage of the human genome that is transcribed, we postulate that for some observed associations the disease phenotype is caused by a structural rearrangement in a regulatory region of the RNA transcript. To identify such mutations, we have performed a genome-wide analysis of all known disease-associated Single Nucleotide Polymorphisms (SNPs) from the Human Gene Mutation Database (HGMD) that map to the untranslated regions (UTRs) of a gene. Rather than using minimum free energy approaches (e.g. mFold), we use a partition function calculation that takes into consideration the ensemble of possible RNA conformations for a given sequence. We identified in the human genome disease-associated SNPs that significantly alter the global conformation of the UTR to which they map. For six disease-states (Hyperferritinemia Cataract Syndrome, β-Thalassemia, Cartilage-Hair Hypoplasia, Retinoblastoma, Chronic Obstructive Pulmonary Disease (COPD), and Hypertension), we identified multiple SNPs in UTRs that alter the mRNA structural ensemble of the associated genes. Using a Boltzmann sampling procedure for sub-optimal RNA structures, we are able to characterize and visualize the nature of the conformational changes induced by the disease-associated mutations in the structural ensemble. We observe in several cases (specifically the 5′ UTRs of FTL and RB1) SNP–induced conformational changes analogous to those observed in bacterial regulatory Riboswitches when specific ligands bind. We propose that the UTR and SNP combinations we identify constitute a “RiboSNitch,” that is a regulatory RNA in which a specific SNP has a structural consequence that results in a disease phenotype. Our SNPfold algorithm can help identify RiboSNitches by leveraging GWAS data and an analysis of the mRNA structural ensemble.

Genome-wide association studies identify mutations in the human genome that correlate with a particular disease. It is common to find mutations associated with disease in the non-coding region of the genome. These non-coding mutations are more difficult to interpret at a molecular level, because they do not affect the protein sequence. In this study, we analyze disease-associated mutations in non-coding regions of our genome in the context of their structural effect on the message of genetic information in our cells, Ribonucleic Acid (RNA). We focus in particular on the regulatory parts of our genes known as untranslated regions. We find that certain disease-associated mutations in these regulatory untranslated regions have a significant effect on the structure of the RNA message. We call these elements “RiboSNitches,” because they act like switches turning on and off genes, but are caused by Single Nucleotide Polymorphisms (SNPs), which are single point mutations in our genome. The RiboSNitches we identify are potentially a new class of pharmaceutical targets, as it is possible to change the structure of RNA with small drug-like molecules.

A scoring system for the classification of beta-thalassemia/Hb E disease severity

Beta-thalassemia intermediate patients show a remarkable clinical heterogeneity. We examined the phenotypic diversity of 950 beta-thalassemia/Hb E patients in an attempt to construct a system for classifying disease severity. A novel scoring system based on six independent parameters, hemoglobin level, age at disease presentation, age at receiving first blood transfusion, requirement for transfusion, spleen size, and growth and development, was able to separate patients into three distinctive severity categories: mild, moderate, and severe courses. This system, therefore, can increase the accuracy of studies of genotype-phenotype interactions and facilitate decisions for appropriate patient management.