Abstract
Background
We aimed to investigate the distribution of selected BCL11A and HMIP polymorphisms (SNP's), and to assess the correlation with HPFH in a cohort of sickle cell patients.
Methods
A preliminary cross‐sectional study was conducted in 102 patients. Group 1 was composed of patients with HPFH and Group 2 consisted of patients without HbF. We assessed 8 SNPs previously associated with HPFH in cohorts genetically close to the Congolese population. Observed frequencies were compared to expected frequencies.
Results
In the group 1, at rs7606173, the observed frequency for the genotype GG was significantly higher and the genotype GC was significantly lower than their respective expected frequencies. At rs9399137, the observed frequency of the genotype TT was significantly lower than expected. Conversely, the observed frequency of the genotype TC was significantly higher than expected. The observed frequency of the genotype TT at rs11886868 was significantly lower than the expected whereas the frequency of the genotype TC was significantly higher than observed. The lowest HbF level was recorded in patients with genotype CC at rs11886868.
Conclusion
In this preliminary study, the results demonstrate that alleles of some of the 8 studied SNPs are not randomly distributed among patients with or without HPFH in this cohort.
Keywords: Africa, Bantu population, BCL11A, Democratic Republic of Congo, HBS1L‐MYB, Kinshasa, polymorphism, sickle cell anemia, steady state
1. Introduction
Sickle Cell Anemia (SCA) is one of the most life threatening conditions in the world.1 About 2.3% of world population is affected and the Democratic Republic of Congo (DRC) is the third most affected country worldwide with an estimated incidence of 40 000 newborns per year.2, 3 Clinical features mainly encompass deadly anemia, painful vaso‐occlusive crises and increased susceptibility to infections.4 However, the severity of these features varies from one patient to another and from one haplotype to another.5 The Bantu haplotype, predominant in the Central Africa, presents the most severe clinical expression of the Sickle Cell Disease.6 A strong correlation has been established between the clinical severity and the level of fetal hemoglobin.5, 7, 8 Classically, the expression of HBG1 (142200) and HBG2 (14250)genes, critical for the synthesis of fetal hemoglobin (HbF), is dramatically reduced shortly before birth and remains as such after birth.7 The residual amount of HbF in adults is usually less than 1% of total hemoglobin.9 Interestingly, in rare individuals, the level of HbF may remain significantly elevated. It is known that an HbF level greater than or equal to 15% is required to inhibit HbS polymerization. This asymptomatic hereditary anomaly is defined as Hereditary Persistence of Fetal Hemoglobin (HPFH).9 Fortunately, the HPFH(141900) was shown to be beneficial to individuals with sickle cell disease. The elevated HbF levels interfere with the polymerization induced by S hemoglobin (HbS) and reduce the Mean Corpuscular HbS concentration.10 By doing so, HPFH(141900) improves the clinical condition for SCA patients. Because of this modulating effect in SCA, multiple studies have been conducted to uncover the underlying mechanism for the inter‐individual variability in HbF values. So far, several quantitative trait loci (QTL) cis and trans to hemoglobin genes have shown significant association with high levels of HbF.11, 12 The BCL11A on chromosome 2p and HBSL1‐MYB intergenic region HMIP on 6q23 are among the most interesting modifiers loci.10, 13
BCL11A is known to be a repressor of the transcription of the γ‐globin gene. In addition to two SNP haplotypes in the enhancer elements, the second intron of BCL11A contains 3 DNase hypersensitive sites (DHS), respectively, located at+62, +58 and +55 kb from the transcription initiation site.14 These sites are important for the regulation of BCL11A expression by erythroid‐specific enhancers. For its part, C‐myb plays a crucial role in the control of the balance of erythroid differentiation and cell proliferation, and regulates the levels of HbF by an unknown mechanism.6, 15, 16 Although the precise role of HBS1L is still poorly understood, polymorphisms in the intergenic region between HBS1L and MYB, known as HBS1L‐MYB Intergenic Polymorphism (HMIP), are significantly associated with the variability in expression of HbF.17
Recently, Fanis and co‐authors, reported 28 SNPs associated with HPFH(141900) including 12 on the BCL11A gene and 16 on the HBS1L‐MYB intergenic region. Interestingly, they pointed out some ethnic variability in the association strength.18, 19, 20 Likewise, Cardoso and co‐authors, also reported an ethnic specific association for rs1427407 in DHS +62 with HbF rates.10
In Central Africa, only the Cameroon SCA patients has been studied. This country is characterized by the predominance of Cameroonian Haplotype.21, 22, 23 Although the DRC, carries a heavy SCA burden, research on SCA is still limited in this area with a predominance of Bantu haplotype. Assessment of QTL's involved in HbF expression has not been performed yet. We aimed to investigate the distribution of selected BCL11A and HMIP polymorphisms, and to assess the correlation with the HPFH(141900) in a cohort of sickle cell Congolese patients living in Kinshasa, the DRC.
2. Methods
2.1. Subjects, study design and case definitions
This cross‐sectional study was conducted in the Sickle cell Centre of Yolo (Kinshasa, DRC). This is the largest and the reference health facility devoted to care for SCA patients in the DRC. During the outpatient clinics, patients were recruited based on the fact that they have SCA, were free of pain and were not transfused within the preceding 100 days as previously suggested.15 We defined HPFH(141900) as fetal hemoglobin value higher than 1%. Patients with HPFH(141900) were assigned to group 1 whereas those without HPFH were allocated to group 2. A total of 102 SCA patients in steady state were recruited including 66 in the group 1 and 36 in the group 2. All patients were homozygous for the β‐globin gene mutation. The mean age of the recruited patients was 23.5±13.7 years. Five ml of peripheral venous blood on EDTA was drawn from each participant.
2.2. Laboratory testing
We performed a standard screening for SCA at the Institut National de Recherche Biomédicale (INRB, Kinshasa/DRC) using semi‐automated agarose gel electrophoresis technique on the Hydrasis II (SEBIA, France) following the manufacturer's instructions. Diagnosis of SCA was retained when the patient harbored mainly HbS with no HbA peaks.
Genomic DNA was extracted locally at the INRB using the standard “salting out” method as previously described.24 DNA samples were later normalized to 50 ηg/μL with a Dropsense® robot (Trinean) at the Center for Human Genetics, KU Leuven, Belgium.
SCA diagnosis was confirmed by PCR and restriction digestion at the Center for Human Genetics. A 440 bp fragment on HBB was amplified by standard PCR using following primers: F‐TGTGGAGCCACACCCTAGGGTTG and R‐CATCAGGAGTGGACAGATCC. The PCR program comprised an initial denaturation for 5 minutes at 95°C; 32 amplification cycles including a short denaturation at 95°C for 30 seconds, annealing at 58°C for 30 seconds and extension at 72°C for 30 seconds. A final extension at 72°C lasted 5 minutes. The control of PCR product was performed electrophoresis on a QIAxcel 3190 (Qiagen Group, Madison, WI, USA). The PCR product was later restricted using DdeI (Roche, Diagnostics, Indianapolis, IN, USA) following a standard protocol. The digestion product was controlled on 2% agarose gel. Normally, this enzyme has two restriction sites (CTGAG/) within the PCR product: one on the SCA mutation spot (E6V) located 201 bp far from the 5′‐end and another 167 nucleotides downstream the mutation site. The normal allele produces three fragments with 201 bp, 167 bp and 72 bp size respectively.
At least 12 SNPs are known to be associated to HPFH(141900). Interestingly, eight of these have been studied in populations genetically close to the Congolese, namely Afro‐Brazilians, African‐American and West‐African.11, 16, 25 Therefore, we included these eight in our SNP panel which contained 4 SNPs in the BCL11A gene (rs11886868, rs766432, rs7606173, rs6706648) and four others on the HBS1L‐MYB intergenic region (rs7776054, rs9399137, rs4895441, rs4895440). Information on primers and PCR product are given in the Table 1.
Table 1.
Description of variants and primers
| Locus | Chr | SNPs | Alleles | Primers | Size (pb) |
|---|---|---|---|---|---|
| BCL11A | 2 | rs766432 | A/C | F :‐CACACCATGGATGAATCCCAGA‐ | 441 |
| rs11886868 | C/T | R :‐TGGTGCTACCCTGAAAGACGG‐ | |||
| rs7606173 | C/G | F :‐ACACCCTGTGATCTTGTGG‐ | 201 | ||
| R :‐GCCAACAGTGATAACCAGC‐ | |||||
| rs6706648 | C/T | F :‐GAAGCTTCCCCTGTCTGCA‐ | 333 | ||
| R :‐TGAGTGCGTATTTGTAAAGTTCC‐ | |||||
| HBS1L‐MYB | 6 | rs7776054 | A/G | F :ATATGCAATATTTGTAATTTGTGTTCTGC‐ | 190 |
| rs9399137 | C/T | R :TTAACTATATCTGTGCACAGAAATACAG‐ | |||
| rs4895441 | A/G | F :‐GGAAACCAGTTTAGAAAGCGTGG‐ | 122 | ||
| rs4895440 | A/T | R :‐TCTCTCTGGATCTCCCTGTC‐ |
DNA fragment encompassing selected SNPs were amplified and Sanger sequenced by Big‐Dye Termination method then analyzed by capillary electrophoresis an ABI 3730xls DNA Analyzer. Sequences were visualized with Sequence Scanner v10 software (ABI) and pairwise alignment was performed with the online NCBI BLAST program (http://blast.ncbi.nlm.nih.gov/Blast.cgi).
2.3. Statistical analyses
Results were manually entered into a microcomputer and analyzed using the Excel Version 2002 (CDC) and they were exported on SPSS 17.0 for further analysis. For each variant, we determined the observed frequencies. From the Hardy Weinberg principle: (p2+2pq+q2=1), we calculated the expected frequencies and frequencies of alleles. Additionally, we determined the minor alleles. For each variant, the observed and expected frequencies were compared using the Chi‐ square test. The distance X2 to test the hypothesis of equality between the observed distribution and the theoretical distribution (null hypothesis or H0) was calculated by summing the Chi‐square two different genotypes of a variant: X2=Σ (Observed frequencies.−Expected frequencies)2/Expected frequencies. The number of degree of freedom (DOF) was 1. This DOF was obtained by the difference between the number of genotypes (three genotypes) and the number of alleles studied variants (two alleles). For 1‐DOF, and an α risk=5%, the χ2 thresholds in a χ2 table is equal to 3.84. When the calculated X2 was less than 3.84, the null hypothesis (H0) was accepted, and we concluded that the population was in equilibrium according the Hardy Weinberg principle. On the other hand, (calculated X2 more than 3.84), H0 was rejected and it was concluded that the population does not follow the Hardy Weinberg principle with an α risk=5%, to be wrong. The observed frequencies of genotypes between the two groups were compared with the Fisher test. A P value<.05 was considered significant.
2.4. Ethical considerations
The study protocol was reviewed and approved by the Internal Review Board of the University of Kinshasa, under the number ESP/CE/027B/2011. Aims and procedures of the study were explained to the participants and we provided answers when they had questions. They were informed about their right to withdraw at any time without further obligation. Privacy was guaranteed to participants. All major participants provided written consent for study participation. Since some participants were minors, their legal representatives provided signed consent for study participation.
3. Results
The HbF level ranged from 4.6% to 33.3% (mean 13.74±6.32%) in the G1.
Table 2 compare the blood‐biochemical variables between the two groups of patients. Compared to group 1, morbidity markers (WBCs, reticulocytes, platelets, CRP and LDH) were higher in group 2 patients without HPFH(141900).
Table 2.
Comparison between the hematological and biochemical variables between the two groups
| Variables | G1 (HbS‐HbF) n=66 | G2 (Hb SS) n=36 | P |
|---|---|---|---|
| HbF (%) | 16.70±8.41 | 0.18±1.06 | <.001 |
| Hb (g/dL) | 9.24±1.43 | 6.45±0.71 | <.001 |
| GB (x103/μL) | 7.94±1.62 | 14.81±4.82 | <.001 |
| Réticulocytes (%) | 7.56±5.03 | 15.47±7.27 | <.001 |
| Plaquettes (×103/μL) | 250.35±94.97 | 360.41±246.85 | .002 |
| CRP (mg/L) | 62.95±24.25 | 207.83±24.26 | <.001 |
| LDH (U/L) | 432.61±156.63 | 1213.67±147.68 | <.001 |
3.1. Variants of the BCL11A gene
The Table 3 summarizes the relationship between observed and expected frequencies of BCL11A variants. According to data analysis, the observed frequencies deviate from the expected theoretical numbers with X2=Σχ2 more than 3.84 between genotypes of all variants of BCL11A, except for the rs11886868 in the group G 1 (Hb SS‐HbF) where the Σχ2 was less than 3.84.
Table 3.
Frequencies of the genotypes of the BCL11A variants
| Locus | Genotypes | G1 (HbS‐HbF) n=66 | G2 (Hb SS) n=36 | |||||
|---|---|---|---|---|---|---|---|---|
| BCL11A | HbF(%) | OF (%) | EF (%) | χ2 | OF (%) | EF(%) | χ2 | |
| rs766432 | AA | 14.03 | 37 | 33.54 | 0.356 | 16 | 34.12 | 9.622 |
| AC | 13.30 | 18 | 21.89 | 0.697 | 14 | 23.73 | 3.989 | |
| CC | 13.41 | 7 | 3.57 | 3.295 | 1 | 4.12 | 2.362 | |
| Σχ2=X2 | 4.342 | Σχ2=X2 | 15.973 | |||||
| rs11886868 | TT | 14.03 | 36 | 35.85 | 0.000 | 16 | 35.62 | 10.806 |
| TC | 14.12 | 20 | 20.26 | 0.003 | 15 | 22.73 | 2.628 | |
| CC | 8.1 | 3 | 2.86 | 0.006 | 0 | 3.62 | 3.62 | |
| Σχ2=X2 | 0.009* | Σχ2=X2 | 17.054 | |||||
| rs7606173 | GG | 15.81 | 36 | 12.11 | 47.128 | 8 | 15.51 | 3.636 |
| GC | 13.59 | 20 | 55.74 | 22.916 | 14 | 22.95 | 7.720 | |
| CC | 13.21 | 10 | 64.10 | 45.660 | 7 | 13.51 | 3.136 | |
| Σχ2=X2 | 115.704 | Σχ2=X2 | 14.492 | |||||
| rs6706648 | CC | 15.76 | 28 | 52.64 | 11.533 | 6 | 19.05 | 8.939 |
| CT | 12.89 | 18 | 42.68 | 14.271 | 20 | 33.87 | 5.679 | |
| TT | 15.1 | 6 | 8.65 | 0.811 | 8 | 15.05 | 3.302 | |
| Σχ2=X2 | 26.615 | Σχ2=X2 | 17.92 | |||||
OF, Observed frequency; EF, Expected frequency; Σχ2=X2; *P<.05 or χ2≤3.84 for 1 degree of freedom.
3.2. Variants of the HBS1L‐MYB intergenic region
The Table 4 shows that the observed frequencies deviate from the expected frequencies with X2=Σχ2 more than 3.84 between genotypes of all variants of HBS1L‐MYB, except for the variant rs9399137 in the group G1(Hb SS‐HbF) and G2 (Hb‐SS) where the Σχ2 was <3.84. The rs4895441 was noted as a AA mutated genotype (major alleles) in this series.
Table 4.
Frequencies of the genotypes of the variants of the HBSL1‐MYB intergenic region
| Locus | Genotypes | G1 (HbS‐HbF) n=66 | G2 (Hb SS) n=36 | |||||
|---|---|---|---|---|---|---|---|---|
| HBS1L‐MYB | HbF (%) | OF(%) | EF(%) | χ2 | OF (%) | EF (%) | χ2 | |
| rs7776054 | AA | 14.7 | 58 | 103.5 | 20.002 | 34 | 64.21 | 8.81 |
| AG | 0 | 0 | 24.96 | 24.96 | 0 | 7.54 | 2.27 | |
| GG | 16.1 | 7 | 1.50 | 20.166 | 2 | 0.22 | 2.21 | |
| Σχ2=X2 | 65.128 | Σχ2=X2 | 13.19 | |||||
| rs9399137 | TT | 14.7 | 44 | 44.44 | 0.004 | 36 | 38.36 | 0.145 |
| TC | 16.08 | 22 | 22.87 | 0.030 | 1 | 1.026 | 0.000 | |
| CC | 0 | 0 | 0.05 | 0.05 | 0 | 0.013 | 0.001 | |
| Σχ2=X2 | 0.084* | Σχ2=X2 | 0.155* | |||||
| rs4895440 | TT | 13.22 | 23 | 41.99 | 8.588 | 16 | 31.99 | 7.992 |
| TA | 13.73 | 25 | 57.97 | 18.751 | 16 | 31.99 | 7.992 | |
| AA | 13.52 | 12 | 20.0 | 3.2 | 4 | 7.99 | 1.992 | |
| Σχ2=X2 | 30.539 | Σχ2=X2 | 17.976 | |||||
| rs4895441 | AA | 13.55 | 65 | 65 | 0 | 36 | 36 | 0 |
| AG | 0 | 0 | 0 | ‐ | 0 | 0 | ‐ | |
| GG | 0 | 0 | 0 | ‐ | 0 | 0 | ‐ | |
| Σχ2=X2 | ‐ | Σχ2=X2 | ‐ | |||||
OF, Observed frequency; EF, Expected frequency; Σχ2=X2; *P<.05 or χ2≤3.84 for 1 degree of freedom.
3.3. Relation between minor allele frequencies
The observed MAFs of the BCL11A variants were lower in G1 compared to G2 with a significant difference recorded for the allele T at rs6706648 (Table 5).
Table 5.
Relation between minor allele frequencies
| Locus | Genotype | Hb SS‐HbF (n=66) | Hb SS (n=36) | P | |||
|---|---|---|---|---|---|---|---|
| BCL11A | HbF (%) | MAF (%) | OF (%) | MAF (%) | OF (%) | ||
| rs766432 | A/C | 13.30 | C (0.24) | 28.8 | C (0.25) | 45.2 | .1 |
| rs11886868 | T/C | 14.12 | C (0.22) | 33.9 | C (0.24) | 51.6 | .1 |
| rs7606173 | G/C | 13.59 | C (0.30) | 30.3 | C (0.48) | 48.3 | .1 |
| rs6706648 | C/T | 12.89 | T (0.28) | 34.6 | T (0.47) | 58.8 | .02 |
| HBS1L‐MYB | |||||||
| rs7776054 | A/G | ‐ | G (0.10) | 0 | G (0.05) | 0 | ‐ |
| rs9399137 | T/C | 16.08 | C (0.05) | 10.8 | C (0.02) | 0 | ‐ |
| rs4895440 | A/G | 13.73 | A (0.40) | 41.7 | A (0.33) | 44.4 | .8 |
| rs4895441 | A/G | ‐ | ‐ | 0 | ‐ | 0 | ‐ |
EF, expected frequencies; OF, observed frequencies.
4. Discussion
In the present report, 8 SNPs at 2 QTL involve in the variability of HbF expression were assessed in 102 Congolese SCA patients. This is the first study of its kind in the Central African region. At each SNP, we counted allele frequency and computed expected genotypes based on Hardy‐Weinberg Laws (HWL). We also analyzed the distribution of genotypes at these eight polymorphic positions between patients with HPFH(141900) (Group 1) and SCA patients without HPFH(141900) (Group 2).
Our study showed that the values of WBCs, reticulocytes, platelets, CRP, and LDH were higher in group 2 of patients without HPFH(141900). This situation is due to the role of fetal hemoglobin (HbF;α2γ2) a major modulator of the clinical and hematologic features of sickle cell anemia. Increased levels of HbF noted in group reduces HbS concentration and retard the polymerization of deoxy sickle hemoglobin, the basis of pathophysiology in sickle cell disease. Their deoxygenated erythrocytes took longer to sickle and did not deform. The consequence is the moderation of the clinical form of the disease, which is reflect by the low levels of these hematologic parameters in group 1 as reported in previous studies worldwide.13, 26
A homogeneous distribution with Hardy‐Weinberg equilibrium, of the rs11886868 (BCL11A) in the G1 group (Hb SS‐HbF) was observed. In addition, the normal homozygous genotype CC of the ancestral allele of rs11886868 variant (BCL11A) (Hb SS‐HbF) was associated with a low rate of HbF (8.1%), while genotypes TT and TC of this variant had similar rates of HbF. The rs11886868 is located in the second intron of BCL11A. The latter is a genetic repressor of the γ globin gene expression which mediates expression of HbF. The variant rs11886868 is the variant that has been most associated with the expression of HbF as the HPFH(141900).11, 12 This inactive variant, associated with SNPCT, act by boosting the synthesis of gamma globin chains.12
For the four BCL11A polymorphisms, the allele C at rs11886868 (BCL11A) was present only in patients with increased fetal hemoglobin (G1). Also, genotype frequencies for rs11886868 showed significant difference between both groups with regard to the HWL (Table 3).
In HBSL1‐MYB intergenic region, a homogeneous distribution of the rs9399137 (HBS1L‐MYB) was observed with the balance of LHW, in the two groups: G 1 (Hb SS‐HbF) et G 2 (Hb SS). The normal genotype (ancestral or wild) CC of this variant was not observed in our cohort. On the other side, the mutated genotype TT was mainly represented in the G 2 (Hb SS).
Independently, G1 presented skewed HWL for rs9399137 whereas G2 deviated from expected genotype counts for rs4895440, although the difference between the two groups was not significant.
These data show that some alleles and genotypes are not randomly distributed between the two groups but are significantly enriched among patients with persistent fetal hemoglobin (Tables 3 and 4). This enforcement of HWL presumably suggests a correlation between the skewed distribution of these SNPs and the distribution of fetal hemoglobin among our patients. Significant associations between rs11886868(BCL11A) and rs9300137(HBS1L‐MYB) the fetal hemoglobin were previously established with a variance effect 11.8% for rs11886868.11, 12, 23, 26, 27 The association rs11886868 (BCL11A) and rs 9300137 (HBS1L‐MYB) with HPFH (141900) has also been reported by other authors in the Sub‐Saharan African population.21, 24, 25, 26, 27, 28, 29, 30
During the analysis, we noticed that among G1 patients, carriers of the allele C at rs9399137 always carried the allele G at rs7776054 and this G‐C haplotype was not found among G2 patients (Table 4). There is possibly a preferential and simultaneous enrichment of the two SNPs. Previously, Uda et al., pointed out that the rs11886868 (BCL11A) was in Linkage Disequilibrium (LD) with some neighboring SNPs.12 Moreover, it is widely known that the African population is the most ancient one, with highest recombination rate and smallest haplotype blocks. We can anticipate that the 2 HBS1L‐MYB SNPs may belong to a block and be associated to HPFH(141900). However, the current study did not target haplotypes. Further studies are needed to deeply investigate this assumption.
We did not encounter certain alleles in our cohort since certain SNPs such as rs7776054 and rs4895441 were homozygous in all patients. This could probably reflect the allele distribution in the general Congolese population.
As a pioneer and preliminary study, our research suggests that alleles at some of studied SNPs are not equally distributed among patients with HPFH (141900) and those without. Thus, this points to a likely association between these polymorphisms and HPFH(141900) in the Congolese population. However, larger studies are needed in order to provide stronger evidence and draw a definite conclusion.
Authors’ Contributions
TMM, JMMM, PTL, KD, GM and VR conceived and designed the study protocol; TMM carried out the clinical assessment; TMM, AL, PTL, JMMM, DKK, KD, GM and VR analysis and interpretation of these data. TMM and MNA performed the review of literature and drafted the manuscript; KD, GM and VR critically revised the manuscript for intellectual content. All authors read and approved the final manuscript. TMM is guarantor of the paper.
Acknowledgments
The authors are grateful to all the participants and their families. We thank all our colleagues involved in the collection of samples, all the nurses of the Sickle Cell Center CMMASS for their support. This research was funded by grant from ALUMNI/KU Leuven.
Mikobi TM, Tshilobo Lukusa P, Aloni MN, et al. Protective BCL11A and HBS1L‐MYB polymorphisms in a cohort of 102 Congolese patients suffering from sickle cell anemia. J Clin Lab Anal. 2018;32:e22207 10.1002/jcla.22207
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