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. 2018 Feb 13;2(3):235-239.
doi: 10.1182/bloodadvances.2017009811.

g(HbF): a genetic model of fetal hemoglobin in sickle cell disease

Affiliations

g(HbF): a genetic model of fetal hemoglobin in sickle cell disease

Kate Gardner et al. Blood Adv. .

Abstract

Fetal hemoglobin (HbF) is a strong modifier of sickle cell disease (SCD) severity and is associated with 3 common genetic loci. Quantifying the genetic effects of the 3 loci would specifically address the benefits of HbF increases in patients. Here, we have applied statistical methods using the most representative variants: rs1427407 and rs6545816 in BCL11A, rs66650371 (3-bp deletion) and rs9376090 in HMIP-2A, rs9494142 and rs9494145 in HMIP-2B, and rs7482144 (Xmn1-HBG2 in the β-globin locus) to create g(HbF), a genetic quantitative variable for HbF in SCD. Only patients aged ≥5 years with complete genotype and HbF data were studied. Five hundred eighty-one patients with hemoglobin SS (HbSS) or HbSβ0 thalassemia formed the "discovery" cohort. Multiple linear regression modeling rationalized the 7 variants down to 4 markers (rs6545816, rs1427407, rs66650371, and rs7482144) each independently contributing HbF-boosting alleles, together accounting for 21.8% of HbF variability (r2) in the HbSS or HbSβ0 patients. The model was replicated with consistent r2 in 2 different cohorts: 27.5% in HbSC patients (N = 186) and 23% in 994 Tanzanian HbSS patients. g(HbF), our 4-variant model, provides a robust approach to account for the genetic component of HbF in SCD and is of potential utility in sickle genetic and clinical studies.

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Conflict of interest statement

Conflict-of-interest disclosure: The authors declare no competing financial interests.

Figures

None
Graphical abstract
Figure 1.
Figure 1.
Flow chart illustrating fate of the initial 892 samples.

References

    1. Platt OS, Brambilla DJ, Rosse WF, et al. Mortality in sickle cell disease. Life expectancy and risk factors for early death. N Engl J Med. 1994;330(23):1639-1644. - PubMed
    1. Platt OS, Thorington BD, Brambilla DJ, et al. Pain in sickle cell disease. Rates and risk factors. N Engl J Med. 1991;325(1):11-16. - PubMed
    1. Steinberg MH. Genetic etiologies for phenotypic diversity in sickle cell anemia. Sci World J. 2009;9:46-67. - PMC - PubMed
    1. Quinn CT, Smith EP, Arbabi S, et al. Biochemical surrogate markers of hemolysis do not correlate with directly measured erythrocyte survival in sickle cell anemia. Am J Hematol. 2016;91(12):1195-1201. - PMC - PubMed
    1. Franco RS, Yasin Z, Palascak MB, Ciraolo P, Joiner CH, Rucknagel DL. The effect of fetal hemoglobin on the survival characteristics of sickle cells. Blood. 2006;108(3):1073-1076. - PMC - PubMed

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