Stacked column graph showing percentage causes of inadequate TCD scans at different ages.

<p>Stacked column graph showing percentage causes of inadequate TCD scans at different ages.</p

Effect of fetal haemoglobin itself and of the genetic HbF modifier variants studied on haematological outcome variables.

<p>Effect of fetal haemoglobin itself and of the genetic HbF modifier variants studied on haematological outcome variables.</p

Number of inadequate scans at each age, with reason for inadequacy.

<p>Number of inadequate scans at each age, with reason for inadequacy.</p

Genotypic values for HbF levels at the three main QTL.

<p>Boxes show the inter-quartile range; the line denotes the median. Whiskers indicate the full range of values observed. P-values are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0197927#pone.0197927.t002" target="_blank">Table 2</a>.</p

Proposed algorithm for management of children with sickle cell disease and inadequate TCD scans.

<p>Proposed algorithm for management of children with sickle cell disease and inadequate TCD scans.</p

Chart showing outcomes on 113 children who had one or more inadequate TCD scan before 3 years of age.

<p>None of these children had overt strokes. SCI: silent cerebral infarction, MRI: magnetic resonance imaging, MRA: magnetic resonance angiography.</p

Variants with significant (p < 0.005) impact on haematological variables in our patients.

<p>Boxes show the inter-quartile range; the line denotes the median. Whiskers indicate the full range of values observed. Individual p-values are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0197927#pone.0197927.t002" target="_blank">Table 2</a>.</p

Percentage of scans in each category in different age groups, showing inadequate results (1a), abnormal velocities (1b), conditional velocities (1c) and normal results (1d).

<p>Percentage of scans in each category in different age groups, showing inadequate results (1a), abnormal velocities (1b), conditional velocities (1c) and normal results (1d).</p

Haplotypes of genetic variants detected at the BCL11A and HMIP loci.

<p>Red letters denote HbF-increasing alleles. HMIP haplotypes were named to match the locus architecture described previously [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0197927#pone.0197927.ref016" target="_blank">16</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0197927#pone.0197927.ref026" target="_blank">26</a>]. A situation with two HbF-raising variants in cis, i.e. occupying the same haplotype, was not observed.</p

A survey of genetic fetal-haemoglobin modifiers in Nigerian patients with sickle cell anaemia

<div><p>Genetic variants at three quantitative trait loci (QTL) for fetal haemoglobin (HbF), <i>BCL11A</i>, <i>HBS1L-MYB</i> and the β-globin gene cluster, have attracted interest as potential targets of therapeutic strategies for HbF reactivation in sickle cell anaemia (SCA). We carried out the first systematic evaluation of critical single nucleotide polymorphisms at these disease modifier loci in Nigerian patients with SCA. Common variants for <i>BCL11A</i> and <i>HBS1L-MYB</i> were strongly associated with HbF levels. At both loci, secondary association signals were detected, illustrating the mapping resolution attainable in this population. For <i>BCL11A</i>, the two independent sites of association were represented by <i>rs1427407</i> (primary site, p = 7.0 x 10⁻¹⁰) and <i>rs6545816</i> (secondary site, conditioned on <i>rs1427407</i>: p = 0.02) and for <i>HBS1L-MYB</i> by <i>rs9402686</i> (<i>HMIP-2B</i>, p = 1.23 x 10⁻⁴) and <i>rs66650371</i> (<i>HMIP-2A</i>, p = 0.002). Haplotype analysis revealed similarities in the genetic architecture of <i>BCL11A</i> and <i>HBS1L-MYB</i> in Nigerian patients. Variants at both loci also alleviated anaemia. The variant allele for the γ globin gene promoter polymorphism <i>XmnI-HBG2</i> was too infrequent in our patients to be evaluated in this relatively small study. Studying the large and diverse SCA patient populations in African countries such as Nigeria will be key for a clearer understanding of how these loci work and for the discovery of new disease modifier genes.</p></div