Identification of novel mechanisms of fetal-haemoglobin induction by common genetic variation in patients with sickle cell disease

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We aim to discover the molecular mechanisms by which benign common DNA variants at two genetic sites, BCL11A and HBS1L-MYB, influence fetal haemoglobin levels in adults. Fetal haemoglobin (HbF) is the oxygen-carrying molecule dominating red blood cells in the unborn. It is switched off around the time of birth and replaced with the adult form of haemoglobin. Since in patients with sickle cell disease (SCD) adult haemoglobin is defective, the ability of some adult patients to produce the fetal form will make the disease significantly milder. Much knowledge has been accumulated regarding the structure and function of the BCL11A and HBS1L-MYB sites. The HbF-affecting genetic variants reside in gene-regulating elements called 'super-enhancers' that control the activity of neighbouring genes in red blood cell precursors and thus affect their development and haemoglobin content. Little is known about how the naturally-occurring DNA changes affect the function of these 'super-enhancers'. Here, we aim to uncover novel regulatory pathways and identify transcription factors binding to genetically-variable enhancer elements. This will add to the arsenal of targets for new therapeutic approaches aiming at reactivating HbF in patients. In addition to guiding new gene therapy strategies, our results will help laying the groundwork for the development of new affordable drugs to benefit the patients suffering from SCD mainly in low-and-middle income countries, especially Africa, where more than 200,000 affected children are born annually. In the UK, the disease is present mostly through the African diaspora and shows significant clinical diversity, partially driven by the variable, genetically-determined presence of HbF. Our experimental strategy will build on three major resources generated through collaboration: (1) four ethnically-diverse groups of well-characterised patients (n > 3,000) from the UK, Tanzania and Nigeria, where we will assemble extensive genetic data; (2) access to 2,000 genetically and haematologically characterised subjects from the TwinsUK cohort, where we will be able to obtain progenitor cells from 16 individuals with specific genetic profiles at BCL11A and HBS1L-MYB and (3) red blood cell producing cell lines carrying individual critical DNA variants generated through genome editing of the red blood cell-producing cell line BEL-A in collaboration with its creator, Prof Jan Frayne.Our principal goals are:(1) to genetically and functionally dissect common genetic variability at the two major quantitative trait loci for fetal-haemoglobin levels, BCL11A and HBS1L-MYB in order to unravel potentially novel molecular mechanisms through which genetic variation controls gene expression, determines HbF levels and influences the generation of red blood cells. A post-doctoral researcher recruited from our collaborators in Tanzania or Nigeria will investigate transcription factor binding (the techniques used will be EMSA - 'electrophoretic mobility shift assays', ChIP - 'chromatin immunoprecipitation') and chromatin looping (a folding of the DNA that occurs in active cells to position regulatory elements next to their target genes, the technique we will use is called '4C-seq') and gene activity in relationship with the genotype of the cells studied.(2) to identify the causal DNA changes at three independent subloci (HMIP-1, HMIP-2B, BCL11A-2) of the above through a combination of genetic mapping and functional studies. From these we will create a genetic score that can be calculated for each patient, aimed at predicting HbF levels and clinical severity in sickle cell disease. This score will become a parameter ascertained in genetic and clinical studies, including drug trials, helping to make such studies more informative;(3) to help build capacity and expertise for sickle cell research in Tanzania and Nigeria through training of researchers and building of extensive genetic datasets for their patient cohorts.