To the editor:

Fetal hemoglobin (HbF) protects against many but not all of the hematologic and clinical complications of sickle cell anemia.1,2  This protection is dependent on the ability of HbF to hinder deoxyHbS polymerization. HbF level is variable and highly heritable. Previous genetic association studies found single nucleotide polymorphisms (SNPs) in regions of BCL11A (chromosome 2p), in the HBS1L-MYB intergenic polymorphism (HMIP; chromosome 6q), and linked to HBB (chromosome 11p) that were associated with HbF (reviewed in Akinsheye et al1 ). Our aim was to perform a meta-analysis of genome-wide association studies (GWAS) to find genetic loci with modest effect sizes that were associated with HbF when a larger sample size was examined.

Common SNPs (585, 563 total) from 7 cohorts totaling 2040 patients were meta-analyzed using the software Meta Analysis Helper (METAL)3  with inverse variance method, where effect estimates are weighted in proportion to their precisions.4  The 7 cohorts included in the meta-analysis are: Cooperative Study of Sickle Cell Disease (CSSCD: n = 841), Multicenter Study of Hydroxyurea (MSH: n = 178), Pulmonary Hypertension and the Hypoxic Response in Sickle Cell Disease (PUSH) study (n = 73), Comprehensive Sickle Cell Centers Collaborative Data (C-data) project (n = 127), Treatment of Pulmonary Hypertension and Sickle Cell Disease with Sildenafil Treatment (Walk-PHaSST) trial (n = 181), Duke University Outcome Modifying Genes study (n = 152), and Silent Infarct Transfusion (SIT) trial (n = 488).

In each of these studies, patients with the HbS only phenotype, aged 5 years or more when HbF was measured were included. None of the patients were treated with hydroxyurea when HbF was measured. The association between HbF and the genotype for each SNP was tested in a multiple linear regression analysis, adjusting for sex and the top 10 principal components, where appropriate. The additive genetic model, which codes the SNP genotype as the number of minor alleles (0,1,2), was assumed. To obtain a normal distribution of the phenotype for analysis the cubic root of HbF was used as the response variable in the regression analysis, as previously established.5 

Table 1 summarizes the results of the meta-analysis for the SNPs that reached genome-wide significance (P < 5 × 10−8). Consistent with previous findings, the most significant SNPs were in BCL11A (lowest P value of 5.36 × 10−58 for rs766432). In addition, 3 SNPs in HMIP reached genome-wide significance. This gene is situated in the interval between the gene HBS1L (a G-protein/elongation factor) and the MYB an erythroid transcription factor, on chromosome 6q23.3, and was previously shown to be associated with HbF in a microarray study.6  SNPs in OR51B5, which were associated with HbF in a previous GWAS,5  did not reach genome-wide significance. These SNPs almost reached genome-wide significance in the CSSCD, but were not significant in other cohorts at α = .05 (supplemental Table 1, available on the Blood Web site; see the Supplemental Materials link at the top of the online letter).

Table 1

Significant SNPs in the meta-analysis

ChromosomeSNPBase pair positionsMinor alleleMAFNBetaSEP valueDirection*Gene
rs766432 60719970 0.276 2038 0.236 0.0147 5.36 × 10−58 +++++++ BCL11A 
rs10195871 60720589 0.313 2027 0.213 0.0144 2.142 × 10−49 +++++++ BCL11A 
rs6706648 60722040 0.395 2004 −0.177 0.0135 3.97 × 10−39 ––––––– BCL11A 
rs6738440 60722241 0.289 1976 −0.158 0.0159 2.945 × 10−23 ––––––– BCL11A 
rs6709302 60727629 0.320 1982 −0.142 0.0147 3.416 × 10−22 ––––––– BCL11A 
rs6732518 60708597 0.323 2035 0.133 0.0156 2.197 × 10−17 +++++++ BCL11A 
rs9494145 135432552 0.070 2039 0.217 0.0258 4.321 × 10−17 +++++++ HMIP 
rs9399137 135419018 0.060 2027 0.236 0.0294 1.172 × 10−15 +++++++ HMIP 
rs4895441 135426573 0.089 2025 0.187 0.0236 2.228 × 10−15 +++++++ HMIP 
rs10184550 60729294 0.319 2040 0.092 0.0147 3.831 × 10−10 +++++++ BCL11A 
rs12477097 60698397 0.364 1976 −0.079 0.0144 4.451 × 10−08 ––––––– BCL11A 
ChromosomeSNPBase pair positionsMinor alleleMAFNBetaSEP valueDirection*Gene
rs766432 60719970 0.276 2038 0.236 0.0147 5.36 × 10−58 +++++++ BCL11A 
rs10195871 60720589 0.313 2027 0.213 0.0144 2.142 × 10−49 +++++++ BCL11A 
rs6706648 60722040 0.395 2004 −0.177 0.0135 3.97 × 10−39 ––––––– BCL11A 
rs6738440 60722241 0.289 1976 −0.158 0.0159 2.945 × 10−23 ––––––– BCL11A 
rs6709302 60727629 0.320 1982 −0.142 0.0147 3.416 × 10−22 ––––––– BCL11A 
rs6732518 60708597 0.323 2035 0.133 0.0156 2.197 × 10−17 +++++++ BCL11A 
rs9494145 135432552 0.070 2039 0.217 0.0258 4.321 × 10−17 +++++++ HMIP 
rs9399137 135419018 0.060 2027 0.236 0.0294 1.172 × 10−15 +++++++ HMIP 
rs4895441 135426573 0.089 2025 0.187 0.0236 2.228 × 10−15 +++++++ HMIP 
rs10184550 60729294 0.319 2040 0.092 0.0147 3.831 × 10−10 +++++++ BCL11A 
rs12477097 60698397 0.364 1976 −0.079 0.0144 4.451 × 10−08 ––––––– BCL11A 

SNPs with P values < 5 × 10−8 are shown.

*

Indicates the direction of association (positive or negative beta estimate) between HbF and single SNPs in each cohort. The order of cohorts compiled in the meta-analysis is as follows: (1) Cooperative Study of Sickle Cell Disease; (2) Pulmonary Hypertension and the Hypoxic Response in Sickle Cell Disease; (3) Multicenter Study of Hydroxyurea; (4) Comprehensive Sickle Cell Centers Collaborative Data project; (5) Treatment of Pulmonary Hypertension and Sickle Cell Disease with Sildenafil Treatment; (6) Duke University Pulmonary Hypertension study; and (7) Silent Infarct Transfusion (SIT) trial.

In the CSSCD cohort, the most significant SNPs in BCL11A (rs766432) and the HMIP region (rs9494145) explained 11.1% and 3.2% of the phenotypic variability in HbF, respectively, and together explain only 14.7% of the variability. Twelve additional SNPs reached statistical significance of 10−5 or less, although none reached genome-wide significance (supplemental Table 1). HbF is regulated as a complex trait and the “missing heritability” not detected by GWAS has various explanations. These include unaccounted gene interactions, large undetected insertions and deletions, epigenetic factors, regulation by small RNAs, and multiple rare variants with small effects.7  For example, SNP rs2033467 in chromosome 5 (supplemental Table 1) is in a novel region but it did not reach genome-wide significance, although it was statistically significant.

Authorship

The online version of this letter contains a data supplement.

Acknowledgments: This work was supported by National Institutes of Health grants R01 HL87681 (M.H.S.), RC2 HL101212 (M.H.S.), HL079915 (M.T.), HL68959 (M.T.), 2R25 HL003679-8 (V.G.), R01 HL079912 (V.G.), 2M01 RR10284-10 (V.G.), 5-UO1-NS042804-07 (M.R.D.), CIDR HHSN268200782096C, U54HL090515 (J.F.C.).

The SickleGen Consortium included: Boston University (H.B., C.T.B., M.H.S., and P.S.); Duke University (M.J.T., A.A.-K., and M.G.); Vanderbilt University and CDC (W.C.H., C.J.B., and M.R.D. for the SIT Study, NCT00072761); Johns Hopkins University (D.E.A., P.B., J.F.C., J.R.K., and E.B.-C. for the SIT Study); PUSH Study (V.G., G.J.K., C.M., J.T., A.C., and L.L.-J. NCT00495638); Children's Hospital Oakland (C.H. representing the Sickle Cell Centers C-Data Project); and The University of Pittsburgh (M.T.G. and Y.Z. representing the Walk-PHAAST investigators NCT00492531; supplemental Table 2).

Conflict-of-interest disclosure: J.F.C. is a consultant to Adventrx Corporation and has received an honorarium and travel expenses from Adventrx Corporation for assisting them with a possible clinical trial of an agent to treat vasooclusive crisis in sickle cell disease. The remaining authors declare no competing financial interests.

Correspondence: Martin H. Steinberg, Department of Medicine, Boston University School of Medicine, 72 E Concord St, Boston, MA 02118; e-mail: mhsteinb@bu.edu.

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