Open access peer-reviewed chapter

Precision Medicine for Sickle Cell Disease: Discovery of Genetic Targets for Drug Development

Written By

Betty S. Pace, Nicole H. Lopez, Xingguo Zhu and Biaoru Li

Reviewed: 06 July 2016 Published: 10 November 2016

DOI: 10.5772/64817

From the Edited Volume

Sickle Cell Disease - Pain and Common Chronic Complications

Edited by Baba Psalm Duniya Inusa

Chapter metrics overview

2,099 Chapter Downloads

View Full Metrics


Sickle cell disease (SCD) consists of inherited monogenic hemoglobin disorders affecting over three million people worldwide. Efforts to establish precision medicine based on the discovery of genetic polymorphisms associated with disease severity are ongoing to inform strategies for novel drug design. Numerous gene mutations have been associated with the clinical complications of SCD such as frequency of pain episodes, acute chest syndrome, and stroke among others. However, these discoveries have not produced additional treatment options. To date, Hydroxyurea remains the only Food and Drug Administration-approved agent for treating adults with SCD; recently it was demonstrated to be safe and effective in children. The main action of Hydroxyurea is the induction of fetal hemoglobin, a potent modifier of SCD clinical severity. Three inherited gene loci including XmnI-HBG2, HBS1L-MYB and BCL11A have been linked to HBG expression, however the greatest progress has been made to develop BCL11A as a therapeutic target. With the expanded availability of next generation sequencing, there exist opportunities to discover additional genetic modifiers of SCD. The progress made over the last two decades to define markers of disease severity and the implications for achieving precision medicine to treat the complications of SCD will be discussed.


  • fetal hemoglobin
  • single nucleotide polymorphism
  • drug discovery
  • genome-wide association studies

1. Introduction

Sickle cell anemia is caused by an A to T point mutation in the sixth codon of the β-globin (HBB) gene on chromosome 11 leading to the production of hemoglobin S (HbSS) during adult development. When the sickle mutation is combined with one of over 400 additional mutations reported in the HBB locus, different subtypes of sickle cell disease (SCD) are produced. For example, heterozygosity for the sickle HBB gene and hemoglobin C produces HbSC disease [1]. A definitive diagnosis of SCD can be made by hemoglobin electrophoresis, isoelectric focusing, or high-performance liquid chromatography. However, DNA testing is required to detect the presence of β-thalassemia mutations, which when inherited with the sickle HBB causes HbS-β0-thalassemia and HbSβ+-thalassemia.

About one in 500 African-American and one in 36,000 Hispanic-American children are born with SCD disease [2], which is diagnosed at birth by newborn screening in the United States. The carrier state or sickle cell trait is detected in 1:13 African Americans and 1:100 Hispanic Americans [3] with an estimated 2.5 million Americans with sickle cell trait [4]. Worldwide about 3.2 million people have SCD and 43 million have sickle cell trait [5] with 80% occurring in sub-Saharan Africa mainly as a protective mechanism against malaria. Moreover, the HBB sickle mutation also occurs in Europe, India, the Arabian Peninsula, and Brazil [6].

Hemoglobin is a tetrameric protein, composed of two α-like and two β-like globin polypeptide chains, which transports oxygen to the body tissues. During human development, two switches in the type of hemoglobin synthesized occur, a process known as hemoglobin switching [1]. The first switch at 6–8 weeks of development involves ε-globin gene silencing and activation of the HBG2 and HBG1 genes throughout fetal erythropoiesis, during which Gγ-globin and Aγ-globin fetal hemoglobin (HbF; α2γ2) are produced. The second switch occurs shortly after birth when the HBG1/HBG2 genes are silenced and HBB is activated. HbF levels decline to <1% of total hemoglobin by 6–12 months of age [7], and HbF is restricted to a population of erythrocytes called F-cells [8]. During hemoglobin switching, the site of hematopoiesis moves from the yolk sac to the liver/spleen and finally the bone marrow, which becomes the main site of hematopoiesis where adult hemoglobin A (HbA, α2β2) is produced in healthy individuals [1]. As the level of HbF decreases around 5–6 months of age, the clinical symptoms of SCD are observed due to high HbS levels and polymerization under deoxygenated conditions producing sickle-shaped red blood cells (RBCs), vascular occlusion, and tissue ischemia. Therefore, precision medicine based on genetic or pharmacologic approaches to maintain high HbF levels is a proven efficacious strategy to treat SCD.


2. Clinical manifestations of sickle cell disease

Over the last 30 years, survival in people living with SCD has improved significantly due to decreased death rates during infancy. However, morbidity remains high due to central nervous system and pulmonary complications during childhood and end-organ damage in adults [9, 10]. The average life expectancy of people with SCD is 50 years in the United States [11]. Individuals with SCD experience a chronic hemolytic anemia caused by HbS polymerization under deoxygenated conditions, which [12] produces RBC membrane damage and a shortened life span of 14–21 days. As a result, HbSS patients have an average hemoglobin level of 6–8 g/dL with an elevated reticulocyte count and plasma lactate dehydrogenase level [13]. Furthermore, the damaged membrane leads to inflexible and dehydrated sickled RBCs and abnormal adhesion to the vascular endothelium producing the vasculopathy observed in persons with SCD [13].

The most common pathophysiology of SCD is vaso-occlusive (VOC) events produced by tissue ischemia leading to pain and acute or chronic injury to the spleen, brain, lungs, kidneys, and bones [13]. Individuals with a severe SCD sub-phenotype have more frequent VOC events, a higher white blood cell count, a lower HbF level, and increased blood vessel flow resistance under deoxygenation conditions [1416]. The most common clinical manifestation of SCD is acute painful episodes which occur mainly in the extremities, but can involve the abdomen, back, and chest [17, 18].

As HbF falls below protective levels at around 6–12 months of age, dactylitis involving pain and swelling of the hands and feet is an early manifestation of SCD and is a risk factor for diseased severity [19]. Splenic sequestration occurs in 30% of children between the ages of 6 months to 3 years, which can cause severe life-threatening anemia and death if not treated promptly. Over time, repeated episodes of VOC in the spleen lead to infarction and a markedly increased risk for infection due to encapsulated bacteria such as Streptococcus pneumonia, Haemophilus influenza, and Staphylococcus aureus among others [20]. To address this significant cause of early mortality, the Prophylactic Penicillin Study I was conducted which demonstrated the ability of prophylactic penicillin to decrease overwhelming sepsis by 90% and improved survival among infants with SCD [21]. This study provided the rationale for establishing newborn screening for SCD in the late 1980s to facilitate the initiation of penicillin prophylaxis in the first few months of life to protect against infection and prevent early mortality. Penicillin prophylaxis has become the standard of care worldwide.

Other types of VOC events include acute chest syndrome [22, 23], silent and acute cerebral infarcts [24, 25], and osteonecrosis of the femoral head. Episodes of acute chest syndrome can be caused by pulmonary VOC, infection, and/or fat emboli from bone marrow infarcts [22]. Long-term damage in the lungs can precede pulmonary hypertension [26] in older children and adults with SCD causing high morbidity and mortality. By adolescents, 50% of individuals with SCD suffer silent cerebral infarcts [27] and 10% of children over the age of 2 experience overt strokes requiring chronic transfusions [28, 29]. The process of VOC can affect any organ system producing a wide variety of complications in SCD involving the heart, liver, gall bladder, kidney, and skin [30].


3. Treatment of vaso-occlusive complications

Blood transfusions are the mainstay of therapy for individuals suffering from acute and chronic complications of SCD. Red blood cell transfusions improve the oxygen-carrying capacity and prevent sickling by decreasing the HbS level to <30% of total hemoglobin [3133]. Transfusions are also used for the acute exacerbation of anemia associated with splenic sequestration and aplastic crisis caused by Parvo B19 virus infection [34]. The most common symptom in persons with SCD is acute and chronic pain due to tissue ischemia, which is correlated with long-term survival [35]. Therefore, early aggressive treatment of pain episodes to prevent complications is the standard of care [36]. Recent research has provided insights into mechanisms of pain related to tissue injury (nociceptive), nerve injury (neuropathic), or unknown causes (idiopathic). Effective pain treatment is most often achieved using opioid narcotics combined with nonsteroidal anti-inflammatory drug.

To address the long-term effects of repeated pain episodes, extensive research has been conducted to develop drugs that induce HbF, which inhibits HbS polymerization [37] to improve the clinical symptoms of SCD. Based on findings in the Multicenter Study of Hydroxyurea [38], this agent is the only Food and Drug Administration-approved drug for the treatment of adults with SCD [39]. Subsequent studies in children including BABY HUG demonstrated that hydroxyurea (HU) is an effective HbF inducer and can be used safely in the first year of life [40]. Unfortunately, HU has a 30% nonresponse rate in adults, causes bone marrow suppression, and has detrimental effects on fertility [38, 41]. Therefore, the development of novel therapeutic agents based on inherited mutations that alter the expression of the HBG1/HBG2 genes to produce high HbF levels is desired to establish precision medicine for SCD.


4. Genetic modifiers of sickle cell disease severity

While homozygosity for the βS-globin gene mutation (HBB; glu6val) causes sickle cell anemia, the clinical diversity of phenotypes and disease severity are similar to the manifestations of multigenic disorders. Intensive studies have been performed to identify genetic risk factors correlated with SCD complications such as stroke, leg ulcers, pulmonary artery hypertension, priapism, and osteonecrosis. To extend the findings of genome-wide association studies of single nucleotide polymorphisms (SNPs) linked with clinical phenotypes, more advanced genomic techniques including next-generation DNA sequencing provide new opportunities to define mechanisms of SCD complications. A comprehensive review of genetic studies conducted in SCD is beyond the scope of this chapter. Therefore, we focus our discussion on efforts to discover SNPs associated with the clinical sub-phenotypes of SCD including pain severity, acute chest syndrome, pulmonary hypertension, osteonecrosis, priapism, leg ulcers, and nephropathy.

4.1. Vaso-occlusive pain

SCD patients experience a wide variety of clinical pain ranging from acute mild/severe to persistent chronic pain. The underlying mechanisms of differences in pain rates are complex and likely involve a number of genetic polymorphisms in several biological systems. Studies have been conducted that provide insights into SNPs associated with the frequency and severity of pain in SCD. Jhun et al. [42] identified mutations in the dopamine D3 receptor (Ser9Gly heterozygotes) associated with a lower acute pain rate. The most commonly used opioid medications including codeine and hydrocodone require cytochrome P450 2D6 (CYP2D6) for drug activation, which can impact the efficacy of these agents. The CYP2D6 gene is highly polymorphic, with variant alleles that result in decreased, absent, or ultra-rapid metabolism [43]. Altered CYP2D6 enzymatic activity in CYP2D6*17 (reduced activity), CYP2D6*5 (gene deletion), and CYP2D6*4 (absent function) is correlated with the analgesic response to codeine and hydrocodone. Therefore, genotyping the CYP2D6 gene is a reasonable approach for developing personalized medicine for the treatment of pain in persons with SCD. Moreover, missense or frame-shift mutations in CYP2C9 decrease or abolish enzymatic activity, respectively, which impairs opioid activation [44, 45]. Likewise, an SNP in the promoter of the gene encoding the enzyme uridine 5′-diphospho (UDP)-glucuronosyltransferase 2B7 (−840G/A) responsible for morphine glucuronidation in the liver is associated with lower morphine metabolites in sickle cell patients suggesting that higher doses of morphine may be required to achieve adequate pain control [46].

4.2. Acute chest syndrome/pulmonary hypertension

Acute chest syndrome continues to contribute to significant morbidity and mortality in children and adults with SCD [47]; therefore, the discovery of genetic modifiers of this complication has the potential for high impact and the design of precision medicine. Redha et al. [48] investigated the association of the vascular endothelial growth factor A (VEGFA) 583C/T mutation with acute chest rates in children with SCD. The presence of the 583T/T genotype was associated with increased serum VEGF levels while the VEGFA 583C/T caused reduced VEGF serum levels.

The rate of RBC hemolysis and release of free heme in the circulation are associated with clinical severity of SCD. Heme oxygenase-1 (HMOX1) is the inducible, rate-limiting enzyme in the catabolism of heme which attenuates the severity of VOC and hemolytic events. The (GT)(n) dinucleotide repeat in the promoter of HMOX1 is highly polymorphic, with long repeats linked to decreased gene activation. Bean et al. [49] examined two HMOX1 promoter polymorphisms including −413A/T and the (GT)(n) microsatellite (with allele (GT)(n) length from 13 to 45 repeats). The length of the (GT)(n) allele was associated with acute chest syndrome, but not pain rates in children with SCD.

Over the last decade, numerous studies have been conducted to define risk factors associated with pulmonary artery hypertension [50, 51], which defines a severe sub-phenotype of SCD leading to premature death. SNPs in genes involved in the regulation of endothelial function, which alter the synthesis of the endothelium-derived vasodilators nitric oxide and prostacyclin, have been implicated [52]. An extended screen of 297 SNPs in 49 candidate genes [53] identified mutations in the transforming growth factor (TGF) superfamily including the activin A type II-like 1 receptor (ACVRL1), bone morphogenetic protein (BMP) receptor 2, bone morphogenetic protein 6, and the β-1 adrenergic receptor (ADRB1) associated with pulmonary artery hypertension. A multiple regression model using age and hemoglobin as covariates demonstrated that SNPs in ACVRL1, BMP6, and ADRB1 independently contribute to pulmonary hypertension risk. These findings offer promise for identifying patients at risk for this complication and developing novel therapeutic targets for SCD.

A recent study by Al-Habboubi et al. [54] examined the association between VEGF secretion and VOC rates among 210 individuals with SCD. Mutations in VEGFA including rs2010963 heterozygous and rs833068 and rs3025020 homozygous states were associated with increased pain rates. Moreover, Yousry et al. [55] observed that the homozygous mutant eNOS 786T/T was significantly associated with a high risk of acute chest syndrome. By contrast, the wild-type eNOS 4a/4b genotype was protective against VOC and pulmonary hypertension while the homozygous haplotype (C, 4a) was significantly associated with the risk of VOC pain, acute chest syndrome, and pulmonary hypertension. Thus, eNOS SNPs may be useful as a genetic marker of prognostic value in SCD to predict a severe disease sub-phenotype.

4.3. Cerebral vascular disease

SCD is the most common cause of ischemic stroke occurring in 10% of children under 15 years of age; by contrast, hemorrhagic strokes are observed more commonly in adults over 30 years of age [56]. Genetic polymorphisms in multiple genes have been implicated in childhood stroke risk. For example, a mutation in vascular adhesion molecule-1 (VCAM1) including the G1238C in the coding region was protective and the intronic T1594C SNP predisposed to small-vessel stroke [5759]. Mutations in the interleukin (IL)4R, tumor necrosis factor (TNF), and ADRB2 genes were found to be independently associated with stroke susceptibility in the large-vessel stroke subgroup, while SNPs in VCAM1 and LDLR NcoI genes were associated with small-vessel stroke risk [59]. Additional genes have been implicated in stroke risk such as the GT-repeat polymorphism in the angiotensinogen gene including alleles A3 and A4, which conferred a fourfold increase in risk [60]. Hoppe et al. [61] identified SNPs in the cystathionine-β-synthase (278thr) and the apoE3 genes that were associated with protection and increased risk for stroke, respectively.

Ischemic stroke is common in children with SCD producing high morbidity and mortality. A meta-analysis by Sarecka-Hujar et al. [62] demonstrated the association of SNP 677C/T in the methylenetetrahydrofolate reductase gene with the risk of stroke. Abnormalities in the coagulation pathway have been implicated in the pathogenesis of cerebral bleeding. For example, protein Z, a vitamin K-dependent glycoprotein structurally related to the vitamin K-dependent coagulation factors, is devoid of catalytic activity and inhibits the generation of thrombin. Mahdi et al. [63] identified three SNPs in the protein Z gene promoter (rs3024718, rs3024719, and rs3024731) and one intronic SNP rs3024735 associated with stroke risk suggesting that reduced protein Z levels produced a procoagulant state and increased risk for thrombotic diseases including ischemic stroke. These studies provide evidence for genetic markers that can be used to assess stroke risk in SCD and targeted for therapeutic intervention.

4.4. Osteonecrosis

Repeated episodes of bone infarction caused by vaso-occlusive events precede osteonecrosis of the head of the femur and humerus, a disabling complication of SCD [64, 65]. The discovery of SNPs in genes involved in bone morphogenesis, metabolism, and vascular disease will identify individuals at high risk for osteonecrosis. Previously, 233 SNPs in seven genes including BMP6, TGFBR2, TGFBR3, EDN1, ERG, KL, and ECE1 were shown to be associated with this complication. There were 18 SNPs in the KL gene, which encodes the glycosyl hydrolase protein that participates in a negative regulatory network of vitamin D metabolism; moreover, 14 SNPs in BMP6 and six SNPs in ANXA2 were significantly associated with osteonecrosis [66]. A second research group [67] demonstrated the association of rs267196 (BMP6) and rs7170178 (ANXA2) with a higher risk of osteonecrosis. However, additional studies are needed to confirm if these markers are predictive of the clinical risk for this complication.

4.5. Priapism

Thirty percent of males with SCD experience the potentially devastating complication of priapism associated with a clinically severe disease sub-phenotype. Proteins involved in neuro-regulatory and adrenergic pathways, nitric oxide biology, and ion channels have been implicated in the pathophysiology of priapism [6871]. More recently, clinical studies have identified genetic markers of priapism that produce erectile dysfunction and determine the ability to respond to phosphodiesterase inhibitors. Nolan et al. [72] identified SNPs in the KLOTHO gene including rs2249358, rs211239, rs211234, and rs211239 associated with an increased risk for priapism among 148 males with SCD. To support these findings, Elliott et al. [69] examined polymorphisms in a second group of adult male SCD patients with a 42% history of priapism. Mutations in the nitric oxide biology (NOS2, NOS3, and SLC4A1) and KLOTHO genes were associated with priapism risk providing further evidence for modulating nitric oxide levels as a therapy for this complication.

4.6. Nephropathy

Sickle nephropathy is a serious complication of SCD that can lead to renal failure and is rapidly becoming a major cause of death in adults. In view of the high medical burden and poor health outcome of end-stage renal disease, genetic markers of nephropathy risk are desirable. Youssry et al. [73] identified soluble FMS-like tyrosine kinase-1, a member of the vascular endothelial growth factor receptor family, as a biomarker for sickle nephropathy. In addition, Ashley-Koch et al. [53] demonstrated that the myosin, heavy chain 9, non-muscle (MYH9), and apolipoprotein L1 (APOL1) genes are associated with risk for focal segmental glomerulosclerosis and end-stage renal disease in African Americans. Seven SNPs in MYH9 and one in APOL1 remained significantly associated with proteinuria after multiple testing corrections. The causative role of these proteins in the development of sickle nephropathy needs to be tested further.

4.7. Leg ulcers

Cutaneous leg ulcers occur more often in adult sickle cell patients with low baseline hemoglobin levels and increased hemolysis rates indicated by high lactate dehydrogenase, bilirubin, and reticulocyte levels. The V34L G/T SNP (rs5985) in the factor XIII gene (F13A1) has been associated with leg ulcers [74]. Other studies have implicated factor V Leiden [75], the fibroblast growth factor receptor [76], and the HLA-B3525 antigen [77] in the pathogenesis of leg ulcers. A larger study involving 243 sickle cell patients [78] examined SNPS in 60 candidate genes that have a putative role in the pathophysiology of SCD. The association of SNPs in KLOTHO, TEK, and the TGF-β/BMP-signaling pathway was implicated in leg ulcer risk. Of these, KLOTHO promotes endothelial nitric oxide production and the TEK receptor tyrosine kinase is involved in angiogenesis. The TGF-β/BMP-signaling pathway modulates wound healing and angiogenesis, among other functions. Hemolysis-driven phenotypes such as leg ulcers could be improved by agents that increase nitric oxide bioavailability.


5. Genetic modifiers of fetal hemoglobin

5.1. HBB locus haplotypes

Inherited genetic mutations that modulate HBG1/HBG2 gene expression enable persons with SCD to maintain high HbF levels, which ameliorates their clinical symptoms and long-term survival [17]. Individual SNPs inherited in set patterns define HBB haplotypes and determine the ancestral origin of the βS-globin gene mutation in different ethnic and racial groups. Five common haplotypes including Senegal, Benin, Central African Republic (Bantu), Cameroon, and Asian (Indian/Saudi-Arabian) have been identified [1]. HbF levels vary greatly among individuals with different and the same HBB haplotype, which has precluded the establishment of a consistent correlation between the two parameters. However, individuals with the Senegal haplotype generally have higher HbF levels and milder disease [79], whereas individuals with the Benin haplotype tend to have lower HbF levels and more severe disease [80]. To address this limitation, a genomic study by Liu et al. [81] established the complexity of the HBB locus providing insights into the challenges of defining distinct HBB haplotypes for the prediction of disease severity and the development of therapeutic strategies.

5.2. Genome-wide association studies (GWAS)

The normal switch from HbF to HbA synthesis occurs during the first year of life reaching adult levels of HbF <1% by 12 months of age. A group of disorders known as hereditary persistence of HbF expression is caused by inherited deletions in the HBB locus or point mutations in the promoter region of the HBG genes. HbF levels range from 10 to 40% depending on whether heterozygous or homogeneous mutations are inherited. To gain insights into loci outside the HBB locus that control HbF heritability, GWAS to identify quantitative trait loci were conducted [82]. Three major loci were discovered including the Xmn1-HBG2 (Gγ-globin) on chromosome 11, HBS1L-MYB intergenic region (HMIP) on chromosome 6q23, and BCL11A gene on chromosome 2p16 that control up to 40% of HbF variance in different populations [83]. These loci will be discussed subsequently in the context of the development of precision medicine for persons with SCD.

5.3. Xmn1-HBG2

In 1985, the C/T SNP at nucleotide −158 of the HBG2 gene (rs7482144; T/T) was shown to be associated with high HbF levels with an increase in HbF expressing erythrocytes or F-cells (Figure 1A), and a milder disease phenotype in persons with SCD and β-thalassemia [84]. The positive association between the rs7482144 minor alleles (C/T) and HbF levels was replicated in European and Native Indian populations. However, this SNP was not associated with HbF levels in the people of African ancestry [85]. By contrast, the rs7482144 (G/A) allele occurred at a higher frequency in sickle cell patients with the Senegal and Arab-Indian haplotypes suggesting that the A allele is associated with the geographical origin of the study population. The ancestry for African Americans with SCD showed a high degree of European, African, and Native American admixture at 39.6, 29.6, and 30.8%, respectively.

Figure 1.

Summary of major single nucleotide polymorphisms (SNPs) associated with inherited genetic modifiers of HbF variance. Genome-wide genetic studies and GWAS identified SNPs associated with inherited levels of HbF in various ethnic and racial groups. Shown are SNPs in the HBB locus (A), the HBS1L-MYB intergenic region (B), and intron 2 of the BCL11A gene (C) associated with HBG regulation.

5.4. HBS1L-MYB (HMIP) region

Early studies conducted in a family of Asian Indian origin using segregation analysis demonstrated a modifier of HBG gene expression independent of the HBB locus [86]. Using a regressive model, a major locus was discovered on chromosome 6q23–q24 in the HMIP region. Of the three SNPs identified, only rs4895441 was significantly associated with HbF levels, explaining 9.2% of variance. Later studies showed an association of the other two SNPs, rs28384513 and rs9399137, with HbF levels in the Northern European population (Figure 1B). Subsequently, these SNPs were also demonstrated to control HbF expression in African American, Brazilian, African British, and Tanzanian sickle cell patients [87]. The minor allele frequency of rs9399137 (C) is most significantly associated with HbF expression, but is less common in African populations, with a frequency of 1–2% in African sickle cell patients without European admixture. Similarly, a 3-bp (TAC) deletion on chromosome 6q23 is common in non-African populations, whereas the minor allele of rs9399137 occurs at a higher frequency in African Americans with SCD and elevated HbF levels [88].

5.5. BCL11A

After the completion of the Human Genome Project and the development of genome-wide techniques, GWAS became the preferred approach to identify inherited genetic modifiers of disease phenotypes. The first GWAS to identify HbF modifiers utilized a selected genotyping study design, targeting 179 individuals with contrasting extremes of F-cell numbers [89]. The Xmn1-HBG2 and HMIP regions were identified along with a novel locus in the second intron of the oncogene BCL11A located at chromosome 2p16; the A allele of rs4671393 was associated with increased HbF levels. Subsequently, Uda et al. [90] confirmed SNPs in the BCL11A gene associated with high HbF in Sardinian thalassemia patients, establishing the first major repressor of HBG1/HBG2 gene expression (Figure 1C). The majority of GWAS to identify inherited HbF determinants in African Americans with SCD have been conducted using samples collected during the Cooperative Study of Sickle Cell Disease [9194]. The first GWAS conducted by Solovieff et al. [93] confirmed the BCL11A SNP (rs766432) and identified a polymorphism in the ORB1B5/OR51B6 locus (rs4910755) associated with HbF levels in sickle cell patients (Figure 1A). A subsequent meta-analysis was conducted using GWAS data generated in seven African-American SCD cohorts totaling 2040 patients [95]. The most significant SNPs were identified in BCL11A (rs766432) and the HMIP region (rs9494145), which represented 11.1 and 3.2% of the phenotypic variability in HbF expression, respectively. Recently, the first GWAS was conducted in a Tanzanian population of 1213 individuals with SCD [96]. Similar to African Americans, SNPs in the BCL11A gene and the HMIP region were replicated in Tanzanians. Other studies have shown up to 10% of HbF variance associated with the BCL11A SNP rs4671393 in sickle cell patients from Northern Brazil (Figure 1C).

5.6. Mechanism of regulating HBG expression

Many decades of research have revealed that two types of mechanisms play a major role in modifying HbF levels: (1) direct transactivation of the HBG1/HBG2 genes through the Xmn1-HBG2 site or (2) an indirect effect on HBG1/HBG2 through the repression of silencers such as BCL11A or MYB. The Xmn1-HBG2 variant rs7482144 mediates a direct effect on Gγ-globin gene expression by functioning as a promoter [1]. By contrast, SNPs in the 14-kb second intron of BCL11A produces a strong enhancement of HbF expression. High levels of the short BCL11A isoform are associated with enhanced HbF expression in primitive erythroblasts, whereas full-length BCL11A isoforms are present in adult-stage erythroblasts when the HBG genes are silenced. BCL11A interacts with several DNA-binding proteins such as the corepressors LSD1/CoREST [97], DNMT1 [98], GATA1/FOG1/NuRD complex [99], and Sox6 [100] to facilitate γ-globin gene silencing through binding in the HbF-silencing region located upstream of the δ-globin gene [101]. Other studies have shown direct binding of BCL11A to a core motif 5′-GGCCGG-3″ in the HBG promoters to form a repressor complex in K562 cells [102]. Recently, an erythroid-specific enhancer was discovered in the second intron of BCL11A [103], which can be targeted to achieve lineage-specific gene silencing to achieve gene therapy for SCD directed at inhibiting BCL11A in erythroid progenitors.

SNP Gene Phenotype Reference
rs1186868 BCL11A Baseline HbF Uda et al. [90]
rs766432 BCL11A Baseline HbF Sedgewick et al. [92]
rs4671393 BCL11A Baseline HbF Lettre et al. [94]
rs7557939 BCL11A Baseline HbF Lettre et al. [94]
rs7482144 HBB Baseline HbF Lettre et al. [94]
rs10128556 HBB Baseline HbF Galarneau et al. [110]
rs3759070 HBE1 Baseline HbF Sebastiani et al. [91]
rs5024042 OR51B5/OR51B6 Baseline HbF Solovieff et al. [93]
rs4895441 HBS1L-MYB Baseline HbF Lettre et al. [94]
rs9494145 HBS1L-MYB Baseline HbF Bae et al. [95]
rs9399137 HBS1L-MYB Baseline HbF Creary et al. [107]
rs28384513 HBS1L-MYB Baseline HbF Galarneau et al. [110]
rs12103880 GLP2R Baseline F-cells Bhatnagar et al. [109]
rs4769058 ALOX5AP HbF induced by HU Sebastiani et al. [91]
rs1867380 AQP9 HbF induced by HU Sebastiani et al. [91]
rs17599586 ARGI HbF induced by HU Ware et al. [108]
rs2295644 ARG2 HbF induced by HU Ware et al. [108]
rs10483802 ARG2 HbF induced by HU Ma et al. [105]
rs2182008 FTL I HbF induced by HU Ma et al. [105]
rs10494225 HAO2 HbF induced by HU Ma et al. [105]
rs7130110 HBE1 HbF induced by HU Sebastiani et al. [91]
rs7977109 NOSI HbF induced by HU Ma et al. [105]
rs944725 NOS2A HbF induced by HU Ma et al. [105]
rs4282891 SAR1A HbF induced by HU Kumkhaek et al. [111]
rs2310991 SAR1A HbF induced by HU Kumkhaek et al. [111]

Table 1.

SNPs known to modulate HbF levels and response to hydroxyurea therapy.

HbF, fetal hemoglobin; HU, hydroxyurea.

The mechanism by which the HMIP region silences HBG expression is less clear. It is known that a 24-kb nonprotein-coding region exists between the HBS1L and MYB oncogenes. A recent study identified a distal regulatory locus HMIP 2, which contains a regulatory element composed of several GATA-1 motifs that coincided with DNaseI-hypersensitive sites associated with intergenic transcripts in erythroid precursor cells [104]. It was suggested that the HMIP 2 element might regulate MYB, which is a repressor of the HGB genes.

5.7. Genetic modifiers of response to hydroxyurea therapy

Data from the Multicenter Hydroxyurea Study [38] suggest that not all persons with SCD respond to HU treatment with increased HbF expression. Therefore, genetic markers to predict response to HU would support the development of precision medicine by limiting unnecessary exposure to a chemotherapy drug that causes bone marrow suppression and decreased fertility [41]. Although limited, studies have identified genetic modifiers of HbF response to HU. For example, SNPs in the ARG2, FLT1, HAO2, and NOS1 genes were associated with increased HbF expression based on HapMap data [105]. Interestingly, 29 genes involved in HU metabolism were located in loci previously reported to be linked to HbF levels including 6q22.3–q23.2, 8q11–q12, and Xp22.2–p22.3 [105, 106]. A novel bioinformatics method Random Forest was used to investigate the association between SNPs and the change in HbF after stable long-term HU therapy. SNPs in the ARG2, FLT1, HAO2, and NOS1 genes and 6q22.3–23.2 and 8q11–q12 regions were associated with the HbF response to HU [105]. A summary of the SNP-associated HBG expression at baseline or in response to HU treatment in sickle cell patients is shown in Table 1 [90-92, 94, 95, 107111].

5.8. MicroRNA-mediated control of HBG gene expression

Recent studies have focused on posttranscriptional mechanisms of HBG regulation via microRNA (miRNA) gene expression. For example, Miller and colleagues [112] demonstrated the ability of LIN28 to silence miRNA let-7 to activate HbF in human primary erythroid progenitors. Likewise, miR-15a and miR-16-1 [113] enhance HBG expression through the inhibition of MYB expression. Studies by Walker et al. correlated miR-26b with baseline HbF levels and miR-151-3p expression with the maximal tolerated dose of HU in children with SCD [114].

Other miRNAs have been implicated in HBG regulation including miR-96 [115], miR-486-3p, miR-210 [116], and miR-34a [117]. Recent studies demonstrated the preferential expression of miR-96 in adult erythroid cells and its ability to directly target the open-reading frame of γ-globin mRNA; the inhibition of miR-96 resulted in a 20% increase in γ-globin expression in erythroid progenitors [115]. BCL11A is directly targeted by miR-486-3p, and its overexpression reduces BCL11A levels followed by an increase in γ-globin expression [118]. The role of MYB as a repressor of γ-globin was demonstrated in children with trisomy 13 where increased miR-15a and miR-16 expression targets MYB expression directly to mediate high HbF levels [113]. By contrast, a subset of miRNAs has been shown to be associated with enhanced γ-globin expression. For example, miR-210 was elevated in a β-thalassemia patient with high HbF expression [116]. Similarly, the Pace group recently demonstrated the ability of miR-34a to exert a positive regulatory effect on the HBG1/HBG2 genes when stably expressed in K562 cells [117] suggesting that these miRNAs target repressor proteins. These studies demonstrate the potential of developing miRNAs as targets for precision medicine and the development of therapeutic options for individuals with SCD.


6. Precision medicine for sickle cell disease

Completion of the Human Genome Project greatly improved efforts to develop gene-based treatment strategies for β-hemoglobinopathies. Early efforts to identify genetic modifiers of clinical severity and sub-phenotypes of disease severity in SCD consisted of candidate gene studies. Insights were gleamed into risk factors for acute VOC pain events such as SNPs in the dopamine D3 receptor [42]. Expanded investigations to understand the wide range of opioid dose required by individual sickle cell patients led to the characterization of mutations in the CYP2D6 gene required for opioid activation and classification of slow, intermediate, and rapid metabolizers [43]. However, additional studies with larger sample sizes and/or direct DNA sequencing are required to develop gene markers of disease severity for the development of precision medicine to inform clinical decision making.

A great urgency exists to identify genetic factors associated with risk for acute chest syndrome, the leading cause of morbidity and mortality in children and adults with SCD. Mutations in VEGF [48] and the HMOX1 [49] genes hold promise since they serve as markers of endothelial damage and hemolysis associated with the release of free heme in the vascular space, respectively. Long-term repeated episodes of acute chest syndrome can lead to pulmonary hypertension and early death. With a paucity of effective therapies for this complication, genetic markers that identify subgroups of sickle cell patients at risk will support efforts to develop precision medicine. For example, SNPs in the TGF superfamily of proteins and the ADRB1gene can be targeted for drug development to improve clinical outcomes. Likewise, SNPs in the eNOS genes [55] required for maintaining normal nitric oxide levels might serve as excellent targets for pharmacologic modulation. Interestingly, SNPs in the KLOTHO [72] and NOS2/NOS3 [69] genes have been associated with the occurrence of priapism in SCD. These observations suggest that developing drug therapy-targeting genes involved in nitric oxide regulation might treat multiple complications of SCD. Genome-wide studies involving next-generation DNA sequencing technology will move the field closer to achieving precision medicine in SCD.

Based on the absence of clinical symptoms in infants and the amelioration of symptoms in persons with hereditary persistence of HbF, the most effective strategy to modulate disease severity in persons with SCD is HBG activation. Therefore, understanding molecular mechanisms of HBG1/HBG1 gene silencing during hemoglobin switching is an attractive but challenging strategy adopted by many investigators over the last three decades. Early genome-wide family genetic studies [82] and subsequent GWAS identified the XmnI-HBG2, HBS1-MYB, and BCL11A loci that account for ~40% of inherited HbF variance [83]. Orkin and colleagues advanced the field significantly by defining mechanisms of BCL11A-mediated γ-globin gene repression during murine development and correction of the SCD phenotype [119]. Genetic studies in an extended family identified mutations in KLF1 that produce hereditary persistence of HbF [120, 121] suggesting this transcription factor is a viable target for gene therapy. However, the efficacy of targeting transcription factors for therapeutic development remains to be demonstrated.

Additional genetic studies that utilize high-throughput DNA (whole genome and exome) and RNA/miRNA (RNA-seq) sequencing will increase our knowledge of mechanisms involved in HBG regulation. With the expanded availability of genome-wide approaches, novel technologies for gene editing, and preclinical mouse models, the translation of bench research findings to clinical trials will be accelerated to improve treatment options for SCD and β-thalassemia.


Funding source

National Heart Lung and Blood Institute, National Institutes of Health to BSP (R01HL069234).


  1. 1. Stamatoyannopoulos G, Grosveld F. Hemoglobin switching. In: Stamatoyannopoulos G, Majerus PW, Perlmutter RM, Varmus H, editors. The Molecular Basis of Blood Disease. Vol. 3. Philadelphia: Saunders. 2001.
  2. 2. September is Sickle Cell Awareness Month. CDC. February 2011.
  3. 3. Sickle Cell Disease and Your Baby. March of Dimes. February 2008.
  4. 4. Vichinsky EP, Mahoney DH, Landlaw SA. Uptodate: Sickle Cell Trait, November 2011.
  5. 5. Global Burden of Disease Study 2013 Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the global burden of disease study 2013. Lancet 386:743–800, 2015.
  6. 6. Silva WS, de Oliveira RF, Ribeiro SB, da Silva IB, de Araújo EM, Baptista AF. Screening for structural hemoglobin variants in Bahia, Brazil. Int J Environ Res Public Health 13:pii(E225), 2016.
  7. 7. Maier-Redelsperger M, Noguchi CT, de Montalembert M, Rodgers GP, Schechter AN, Gourbil A, Blanchard D, Jais JP, Ducrocq R, Peltier JY. Variation in fetal hemoglobin parameters and predicted hemoglobin S polymerization in sickle cell children in the first two years of life: Parisian Prospective Study on Sickle Cell Disease. Blood 84:3182–8, 1984.
  8. 8. Boyer SH, Belding TK, Margolet L, Noyes AN. Fetal hemoglobin restriction to a few erythrocytes (F cells) in normal human adults. Science 188:361–3, 1975.
  9. 9. Hassell KL. Population estimates of sickle cell disease in the U.S. Am J Prev Med 38:S512–21, 2010.
  10. 10. Manci EA, Culberson DE, Yang YM, Gardner TM, Powell R, Haynes J Jr, Shah AK, Mankad VN. Investigators of the Cooperative Study of Sickle Cell Disease. Causes of death in sickle cell disease: an autopsy study. Br J Haematol 123:359–65, 2003.
  11. 11. Werner EM. NHLBI Activities in Hemoglobinopathies. National Heart Blood and Lung Institute/National Institute of Health. NICHD Newborn Screening Translational Research Network Meeting. pp. 1–38, 2013.
  12. 12. Quinn CT. Clinical severity in sickle cell disease: the challenges of definition and prognostication. Exp Biol Med 241:679–88, 2016.
  13. 13. Bender MA, Seibel GD. Sickle Cell Disease. 2003 Sep 15 [Updated 2014 Oct 23]. In: Pagon RA, Adam MP, Ardinger HH, et al., editors. GeneReviews® [Internet]. Seattle (WA): University of Washington, Seattle; 1993–2016. Available from:
  14. 14. Charache S, Barton FB, Moore RD, Terrin ML, Steinberg MH, Dover GJ, Ballas SK, McMahon RP, Castro O, Orringer EP. Hydroxyurea and sickle cell anemia. Clinical utility of a myelosuppressive “switching” agent. The multicenter study of hydroxyurea in sickle cell anemia. Medicine 75:300–26, 1996.
  15. 15. Darbari DS, Onyekwere O, Nouraie M, Minniti CP, Luchtman-Jones L, Rana S, Sable C, Ensing G, Dham N, Campbell A, Arteta M, Gladwin MT, Castro O, Taylor JG 6th, Kato GJ, Gordeuk V. Markers of severe vaso-occlusive painful episode frequency in children and adolescents with sickle cell anemia. J Pediatr 160:286–90, 2012.
  16. 16. Wood DK, Soriano A, Mahadevan L, Higgins JM, Bhatia SN. A biophysical indicator of vaso-occlusive risk in sickle cell disease. Sci Transl Med 4:123ra26, 2014.
  17. 17. Platt OS, Thorington BD, Brambilla DJ, Milner PF, Rose WF, Vichinsky E, Kinney TR. Pain in sickle cell disease. Rates and risk factors. N Eng J Med 325:11–6, 1991.
  18. 18. Gill FM, Sleeper LA, Weiner SJ, Brown AK, Bellevue R, Grover R, Pegelow CH, Vichinsky E. Clinical events in the first decade in a cohort of infants with sickle cell disease. Cooperative study of sickle cell disease. Blood 86:776–83, 1995.
  19. 19. Miller ST, Sleeper LA, Pegelow CH, Enos LE, Wang WC, Weiner SJ, Wethers DL, Smith J, Kinney TR. Prediction of adverse outcomes in children with sickle cell disease. N Engl J Med 342:83–9, 2000.
  20. 20. Powars D, Overturf G, Weiss J, Lee S, Chan L. Pneumococcal septicemia in children with sickle cell anemia. Changing trend of survival. JAMA 245:1839–42, 1981.
  21. 21. Cober MP, Phelps SJ. Penicillin prophylaxis in children with sickle cell disease. J Pediatr Pharmacol Ther 15:152–159, 2010.
  22. 22. Vichinsky EP, Neumayr LD, Earles AN, Williams R, Lennette ET, Dean D, Nickerson B, Orringer E, McKie V, Bellevue R, Daeschner C, Manci EA. Causes and outcomes of the acute chest syndrome in sickle cell disease. National Acute Chest Syndrome Study Group. N Engl J Med 342:1855–65, 2000.
  23. 23. Vichinsky EP, Styles LA, Colangelo LH, Wright EC, Castro O, Nickerson B. Acute chest syndrome in sickle cell disease. Clinical presentation and course. Cooperative Study of Sickle Cell Disease. Blood 89:1787–92, 1997.
  24. 24. DeBaun MR, Gordon M, McKinstry RC, Noetzel MJ, White DA, Sarnaik SA, Meier ER, Howard TH, Majumdar S, Inusa BPD, Telfer PT, Kirby-Allen M, McCavit TL, Kamdem A, Airewele G, Woods GM, Berman B, Panepinto JA, Fuh, BR, Kwiatkowski JL, King AA, Fixler JM, Rhodes MM, Thompson AA, Heiny ME, Redding-lallinger RC, Kirkham FJ, Dixon N, Gonzalez CE, Kalinyak KA, Quinn CT, Strouse JJ, Miler JP, Lehmann H, Kraut MA, Ball Jr. WS, Hirtz D, Casella JF. Controlled trial of transfusion for silent cerebral infarcts in sickle cell anemia. N Engl Med 371:699–710, 2014.
  25. 25. Meier ER, Wright EC, Miller JL. Reticulocytosis and anemia are associated with an increased risk of death and stoke in the newborn cohort of the Cooperative Study of Sickle Cell Disease. Am J Hematol 89:904–6, 2014.
  26. 26. Ataga KI, Moore CG, Jones S, Olajide O, Strayhorn D, Hinderliter A, Orringer EP. Pulmonary hypertension in patients with sickle cell disease: a longitudinal study. Br J Haematol 134:109–15, 2006.
  27. 27. Bernaudin F, Verlhac S, Arnaud C, Kamdem A, Chevret S, Hau I, Coïc L, Leveillé E, Lemarchand E, Lesprit E, Abadie I, Medejel N, Madhi F, Lemerle S, Biscardi S, Bardakdjian J, Galactéros F, Torres M, Kuentz M, Ferry C, Socié G, Reinert P, Delacourt C. Impact of early transcranial Doppler screening and intensive therapy on cerebral vasculopathy outcome in newborn sickle cell anemia cohort. Blood 117:1130–40, 2011.
  28. 28. Schatz J, Brown RT, Pascual JM, Hsu L, DeBaun MR. Poor school and cognitive functioning with silent cerebral infarcts and sickle cell disease. Neurology 56:1109–11, 2001.
  29. 29. Pegelow CH, Macklin EA, Moser FG, Wang WC, Bello JA, Miller ST, Vichinsky EP, DeBaun MR, Guarini L, Zimmerman RA, Younkin DP, Gallagher DM, Kinney TR. Longitudinal changes in brain magnetic resonance imaging findings in children with sickle cell disease. Blood 99:3014–8, 2002.
  30. 30. Bonds DR. Three decades of innovation in the management of sickle cell disease: the road to understanding the sickle cell disease clinical phenotype. Blood Rev 19:99–110, 2005.
  31. 31. Reed W, Vichinsky E. New considerations in the treatment of sickle cell disease. Annu Rev Med 49:461–74, 1998.
  32. 32. Nifong T, Domen R. Oxygen saturation and hemoglobin a content in patients with sickle cell disease undergoing erythrocytapheresis. Ther Apher 6:390–3, 2002.
  33. 33. Thurston G, Henderson N, Jeng M. Effects of erythrocytapheresis transfusion on the viscoelasticity of sickle cell blood. Clin Hemorheol Microcirc 30:83–97, 2004.
  34. 34. Josephson CD, Su LL, Hillyer KL, Hillyer CD. Transfusions in the patient with sickle cell disease: a critical review of the literature and transfusion guidelines. Transfusion Med Rev 21:118–33, 2007.
  35. 35. Platt OS. Easing the suffering caused by sickle cell disease. N Engl J Med 330:783–4, 1994.
  36. 36. Benjamin L. Pain management in sickle cell disease: palliative care begins at birth? Am Soc Hematol 1:466–74, 2008.
  37. 37. Fard AD, Hosseini SA, Shahjahani M, Salari F, Jaseb K. Evaluation of novel fetal hemoglobin inducer drugs in treatment of β-hemoglobinopathy disorder. Int J Hematol Oncol Stem Cell Res 7:47–54, 2013.
  38. 38. Charache S, Terrin ML, Moore RD, Dover GJ, Barton FB, Eckert SV, McMahon RP, Bonds DR. Effect of hydroxyurea on the frequency of painful crises in sickle cell anemia. Investigators of the Multicenter Study of Hydroxyurea in Sickle Cell Anemia. N Engl J Med 332:1317–22, 1995.
  39. 39. Wong TE, Brandow AM, Lim W, Lottenberg R. Update on the use of hydroxyurea therapy in sickle cell disease. Blood 124:3850–7, 2014.
  40. 40. Wang WC, Ware RE, Miller ST, Iyer RV, Casella JF, Minniti CP, Rana S, Thornburg CD, Rogers ZR, Kalpatthi RV, Barredo JC, Brown RC, Sarnaik SA, Howard TH, Wynn LW, Kutlar A, Armstrong FD, Files BA, Goldsmith JC, Waclawiw MA, Huang X, Thompson BW; BABY HUG investigators. Hydroxycarbamide in very young children with sickle-cell anaemia: a multicentre, randomised, controlled trial (BABY HUG). Lancet 377:1663–72, 2011.
  41. 41. Steinberg MH, Lu ZH, Barton FB, Terrin ML, Charache S, Dover GJ. Fetal hemoglobin in sickle cell anemia: determinants of response to hydroxyurea. Multicenter Study of Hydroxyurea. Blood 89:1078–88, 1997.
  42. 42. Jhun E, He Y, Yao Y, Molokie RE, Wilkie DJ, Wang ZJ. Dopamine D3 receptor Ser9Gly and catechol-o-methyltransferase Val158Met polymorphisms and acute pain in sickle cell disease. Anesth Analg 119:1201–7, 2014.
  43. 43. Yee MM, Josephson C, Hill CE, Harrington R, Castillejo MI, Ramjit R, Osunkwo I. Cytochrome P450 2D6 polymorphisms and predicted opioid metabolism in African American children with sickle cell disease. J Pediatr Hematol Oncol 35:e301–5, 2013.
  44. 44. Jaja C, Bowman L, Wells L, Patel N, Xu H, Lyon M, Kutlar A. Preemptive genotyping of CYP2C8 and CYP2C9 allelic variants involved in NSAIDs metabolism for sickle cell disease pain management. Clin Transl Sci 8:272–80, 2015.
  45. 45. Jaja C, Patel N, Scott SA, Gibson R, Kutlar A. CYP2C9 allelic variants and frequencies in a pediatric sickle cell disease cohort: implications for NSAIDs pharmacotherapy. Clin Transl Sci 7:396–401, 2014.
  46. 46. Darbari DS, van Schaik RH, Capparelli EV, Rana S, McCarter R, van den Anker J. UGT2B7 promoter variant -840G>A contributes to the variability in hepatic clearance of morphine in patients with sickle cell disease. Am J Hematol 83:200–2, 2008.
  47. 47. Vichinsky EP, Neumayr LD, Earles AN, et al. Causes and outcomes of the acute chest syndrome in sickle cell disease. N Engl J Med 342:1855–65, 2000.
  48. 48. Redha NA, Mahdi N, Al-Habboubi HH, Almawi WY. Impact of VEGFA -583C > T polymorphism on serum VEGF levels and the susceptibility to acute chest syndrome in pediatric patients with sickle cell disease. Pediatr Blood Cancer 61:2310–2, 2014.
  49. 49. Bean CJ, Boulet SL, Ellingsen D, Pyle ME, Barron-Casella EA, Casella JF, Payne AB, Driggers J, Trau HA, Yang G, Jones K, Ofori-Acquah SF, Hooper WC, DeBaun MR. Heme oxygenase-1 gene promoter polymorphism is associated with reduced incidence of acute chest syndrome among children with sickle cell disease. Blood 120:3822–8, 2012.
  50. 50. Kato GJ, Onyekwere OC, Gladwin MT. Pulmonary hypertension in sickle cell disease: relevance to children. Pediatr Hematol Oncol 24:159–70, 2007.
  51. 51. Potoka KP, Gladwin MT. Vasculopathy and pulmonary hypertension in sickle cell disease. Am J Physiol Lung Cell Mol Physiol 308:L314–24, 2015.
  52. 52. Bunn HF, Nathan DG, Dover GJ, Hebbel RP, Platt OS, Rosse WF, Ware RE. Pulmonary hypertension and nitric oxide depletion in sickle cell disease. Blood 116:687–92, 2010.
  53. 53. Ashley-Koch AE, Elliott L, Kail ME, De Castro LM, Jonassaint J, Jackson TL, Price J, Ataga KI, Levesque MC, Weinberg JB, Orringer EP, Collins A, Vance JM, Telen MJ. Identification of genetic polymorphisms associated with risk for pulmonary hypertension in sickle cell disease. Blood 111:5721–6, 2008.
  54. 54. Al-Habboubi HH, Mahdi N, Abu-Hijleh TM, Abu-Hijleh FM, Sater MS, Almawi WY. The relation of vascular endothelial growth factor (VEGF) gene polymorphisms on VEGF levels and the risk of vasoocclusive crisis in sickle cell disease. Eur J Haematol 89:403–9, 2012.
  55. 55. Yousry SM, Ellithy HN, Shahin GH. Endothelial nitric oxide synthase gene polymorphisms and the risk of vasculopathy in sickle cell disease. Hematology 4:1–9, 2016.
  56. 56. Ohene-Frempong K, Weiner SJ, Sleeper LA, Miller ST, Embury S, Moohr JW, Wethers DL, Pegelow CH, Gill FM. Cerebrovascular accidents in sickle cell disease: rates and risk factors. Blood 91:288–94, 1998.
  57. 57. Belisário AR, Nogueira FL, Rodrigues RS, Toledo NE, Cattabriga AL, Velloso-Rodrigues C, Duarte FO, Silva CM, Viana MB. Association of alpha-thalassemia, TNF-alpha (-308G>A) and VCAM-1 (c.1238G>C) gene polymorphisms with cerebrovascular disease in a newborn cohort of 411 children with sickle cell anemia. Blood Cells Mol Dis 54:44–50, 2015.
  58. 58. Taylor JG 6th, Tang DC, Savage SA, Leitman SF, Heller SI, Serjeant GR, Rodgers GP, Chanock SJ. Variants in the VCAM1 gene and risk for symptomatic stroke in sickle cell disease. Blood 100:4303–9, 2002.
  59. 59. Hoppe C, Klitz W, Cheng S, Apple R, Steiner L, Robles L, Girard T, Vichinsky E, Styles L; CSSCD Investigators. Gene interactions and stroke risk in children with sickle cell anemia. Blood 103:2391–6, 2004.
  60. 60. Tang DC, Prauner R, Liu W, Kim KH, Hirsch RP, Driscoll MC, Rodgers GP. Polymorphisms within the angiotensinogen gene (GT-repeat) and the risk of stroke in pediatric patients with sickle cell disease: a case-control study. Am J Hematol 68:164–9, 2001.
  61. 61. Hoppe C, Cheng S, Grow M, Silbergleit A, Klitz W, Trachtenberg E, Erlich H, Vichinsky E, Styles L. A novel multilocus genotyping assay to identify genetic predictors of stroke in sickle cell anaemia. Br J Haematol 114:718–20, 2001.
  62. 62. Sarecka-Hujar B, Kopyta I, Pienczk-Reclawowicz K, Reclawowicz D, Emich-Widera E, Pilarska E. The TT genotype of methylenetetrahydrofolate reductase 677C>T polymorphism increases the susceptibility to pediatric ischemic stroke: meta-analysis of the 822 cases and 1,552 controls. Mol Biol Rep 39:7957–63, 2012.
  63. 63. Mahdi N, Abu-Hijleh TM, Abu-Hijleh FM, Sater MS, Al-Ola K, Almawi WY. Protein Z polymorphisms associated with vaso-occlusive crisis in young sickle cell disease patients. Ann Hematol 91:1215–20, 2012.
  64. 64. Milner PF, Kraus AP, Sebes JI, Sleeper LA, Dukes KA, Embury SH, Bellevue R, Koshy M, Moohr JW, Smith J. Sickle cell disease as a cause of osteonecrosis of the femoral head. N Engl J Med 325:1476–81, 1991.
  65. 65. Almeida A, Roberts I. Bone involvement in sickle cell disease. Br J Haematol 129:482–90, 2005.
  66. 66. Baldwin C, Nolan VG, Wyszynski DF, Ma QL, Sebastiani P, Embury SH, Bisbee A, Farrell J, Farrer L, Steinberg MH. Association of KLOTHO, bone morphogenic protein 6, and annexin A2 polymorphisms with sickle cell osteonecrosis. Blood 106:372–5, 2005.
  67. 67. Chaouch L, Kalai M, Jbara MB, Chaabene AB, Darragi I, Chaouachi D, Mallouli F, Hafsia R, Ghanem A, Abbes S. Association between rs267196 and rs267201 of BMP6 gene and osteonecrosis among sickle cell anaemia patients. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub 159:145–9, 2005.
  68. 68. Chrouser KL, Ajiboye OB, Oyetunji TA, Chang DC. Priapism in the United States: the changing role of sickle cell disease. Am J Surg 201:468–74, 2011.
  69. 69. Elliott L, Ashley-Koch AE, De Castro L, Jonassaint J, Price J, Ataga KI, Levesque MC, Brice Weinberg J, Eckman JR, Orringer EP, Vance JM, Telen MJ. Genetic polymorphisms associated with priapism in sickle cell disease. Br J Haematol 137:262–7, 2007.
  70. 70. Rogers ZR. Priapism in sickle cell disease. Hematol Oncol Clin North Am 19:917–28, 2005.
  71. 71. Broderick GA. Priapism and sickle-cell anemia: diagnosis and nonsurgical therapy. J Sex Med 9:88–103, 2012.
  72. 72. Nolan VG, Baldwin C, Ma Q, Wyszynski DF, Amirault Y, Farrell JJ, Bisbee A, Embury SH, Farrer LA, Steinberg MH. Association of single nucleotide polymorphisms in KLOTHO with priapism in sickle cell anaemia. Br J Haematol 128:266–72, 2005.
  73. 73. Youssry I, Makar S, Fawzy R, Wilson M, AbdAllah G, Fathy E, Sawires H. Novel marker for the detection of sickle cell nephropathy: soluble FMS-like tyrosine kinase-1 (sFLT-1). Pediatr Nephrol 30:2163–8, 2015.
  74. 74. Gemmati D, Tognazzo S, Serino ML, Fogato L, Carandina S, De Palma M, Izzo M, De Mattei M, Ongaro A, Scapoli GL, Caruso A, Liboni A, Zamboni P. Factor XIII V34L polymorphism modulates the risk of chronic venous leg ulcer progression and extension. Wound Repair Regen 12:512–7, 2004.
  75. 75. Brandt HRC, Messina MCD, Belda W, Martins JEC, Criado PR. Leg ulcers associated with factor V Leiden and prothrombin G20210A and methyltetrahydrofolate reductase mutations: successful treatment with warfarin. Int J Dermatol 46:1319–20, 2007.
  76. 76. Nagy N, Németh IB, Szabad G, Szolnoky G, Belsõ N, Bata-Csörgõ Z, Dobozy A, Kemény L, Széll M. The altered expression of syndecan 4 in the uninvolved skin of venous leg ulcer patients may predispose to venous leg ulcer. Wound Repair Regen 16:495–502, 2008.
  77. 77. Ofosu MD, Castro O, Alarif L. Sickle cell leg ulcers are associated with HLA-B35 and Cw4. Arch Dermatol 123:482–4, 1987.
  78. 78. Nolan VG, Adewoye A, Baldwin C, Wang L, Ma Q, Wyszynski DF, Farrell JJ, Sebastiani P, Farrer LA, Steinberg MH. Sickle cell leg ulcers: associations with haemolysis and SNPs in KLOTHO, TEK and genes of the TGF-beta/BMP pathway. Br J Haematol 133:570–8, 2006.
  79. 79. Nagel RL, Erlingsson S, Fabry ME, Fabry ME, Croizat H, Susuka SM, Lachman H, Sutton M, Driscoll C, Bouhassira E, Billett, HH. The Senegal DNA haplotype is associated with the amelioration of anemia in African-American sickle cell anemia patients. Blood 77:1371–5, 1991.
  80. 80. Powars DR. 1990. Sickle cell anemia and major organ failure. Hemoglobin 14:573–98.
  81. 81. Liu Li, Onykwere O, Quinn, C Sylvan C, Kalra I, Muralidar S, Amekar S, Pace BS. High density SNP-chip genotyping and haploview analysis to define γ-globin locus haplotypes. Blood Cell Mol Dis 42:16–24, 2009.
  82. 82. Menzel S, Garner C, Gut I, Matsuda F, Yamaguchi M, Heath S, Foglio M, Zelenika D, Boland A, Rooks H. et al. A QTL influencing F cell production maps to a gene encoding a zinc-finger protein on chromosome 2p15. Nat Genet 39:1197–9, 2007.
  83. 83. Thein SL, Menzel S, Lathrop M, Garner C. Control of fetal hemoglobin: new insights merging from genomics and clinical implications. Hum Mol Genet 18:216–23. 2009.
  84. 84. Labie D, Dunda-Belkhodja O, Rouabhi F, Pagnier J, Ragusa A, Nagel RL. The -158 site 50 to the Gg gene and Gg expression. Blood 66:1463–5, 1985.
  85. 85. Efremov GD, Gjorgovski I, Stojanovski N, Diaz-Chico JC, Harano T, Kutlar F, Huisman THJ. One haplotype is associated with the Swiss type of hereditary persistence of fetal hemoglobin in the Yugoslavian population. Hum Genet 77:132–6, 1987.
  86. 86. Thein SL, Weatherall DJ. A non-deletion hereditary persistence of fetal hemoglobin (HPFH) determinant not linked to the beta-globin gene complex. Prog Clin Biol Res 316B: 97–111, 1989.
  87. 87. Pissard S, Beuzard Y. A potential regulatory region for the expression of fetal hemoglobin in sickle cell disease. Blood 84:331–8, 1994.
  88. 88. Old JM, Ayyub H, Wood WG, Clegg JB, Weatherall DJ. Linkage analysis of nondeletion hereditary persistence of fetal hemoglobin. Science 215:981–2, 1982.
  89. 89. Thein SL, Menzel S, Peng X, Best S, Jiang J, Close J, Silver N, Gerovasilli A, Ping C, Yamaguchi M, Wahlberg K, Ulug P, Spector TD, Garner C, Matsuda F, Farrall M, Lathrop M. Intergenic variants of HBS1L-MYB are responsible for a major quantitative trait locus on chromosome 6q23 influencing fetal hemoglobin levels in adults. Proc Natl Acad Sci 104:11346–51, 2007.
  90. 90. Uda M, Galanello R, Sanna S, Lettre G, Sankaran VG, Chen W, Usala G, Busonero F, Maschio A, Albai G, Piras MG, Sestu N, Lai S, Dei M, Mulas A, Crisponi L, Naitza S, Asunis I, Deiana M, Nagaraja R, Perseu L, Satta S, Cipollina MD, Sollaino C, Moi P, Hirschhorn JN, Orkin SH, Abecasis GR, Schlessinger D, Cao A. Genome-wide association study shows BCL11A associated with persistent fetal hemoglobin and amelioration of the phenotype of beta-thalassemia. Proc Natl Acad Sci USA 105:1620–5, 2008.
  91. 91. Sebastiani P, Wang L, Nolan VG, Melista E, Ma Q, Baldwin CT, Steinberg MH. Fetal hemoglobin in sickle cell anemia: Bayesian modeling of genetic associations. Am J Hematol 83:189–95, 2008.
  92. 92. Sedgewick AE, Timofeev N, Sebastiani P, So JC, Ma ES, Chan LC, Fucharoen G, Fucharoen S, Barbosa CG, Vardarajan BN, Farrer LA, Baldwin CT, Steinberg MH, Chui DH. BCL11A is a major HbF quantitative trait locus in three different populations with beta-hemoglobinopathies. Blood Cells Mol Dis 41:255–8, 2008.
  93. 93. Solovieff N, Milton JN, Hartley SW, Sherva R, Sebastiani P, Dworkis DA, Klings ES, Farrer LA, Garrett ME, Ashley-Koch A, Telen MJ, Fucharoen S, Ha SY, Li CK, Chui DH, Baldwin CT, Steinberg MH. Fetal hemoglobin in sickle cell anemia: genome-wide association studies suggest a regulatory region in the 5' olfactory receptor gene cluster. Blood 115:1815–22, 2010.
  94. 94. Lettre G, Sankaran VG, Bezerra MA, Araujo AS, Uda M, Sanna S, Cao A, Schlessinger D, Costa FF, Hirschhorn JN, Orkin SH. DNA polymorphisms at the BCL11A, HBS1L-MYB, and beta-globin loci associate with fetal hemoglobin levels and pain crises in sickle cell disease. Proc Natl Acad Sci 105:11869–74, 2008.
  95. 95. Bae HT, Baldwin CT, Sebastiani P, Telen MJ, Ashley-Koch A, Garrett M, Hooper WC, Bean CJ, Debaun MR, Arking DE, Bhatnagar P, Casella JF, Keefer JR, Barron-Casella E, Gordeuk V, Kato GJ, Minniti C, Taylor J, Campbell A, Luchtman-Jones L, Hoppe C, Gladwin MT, Zhang Y, Steinberg MH. Meta-analysis of 2040 sickle cell anemia patients: BCL11A and HBS1L-MYB are the major modifiers of HbF in African Americans. Blood 120:1961–2, 2012.
  96. 96. Mtatiro SN, Singh T, Rooks H, Mgaya J, Mariki H, Soka D, Mmbando B, Msaki E, Kolder I, Thein SL, Menzel S, Cox SE, Makani J, Barrett JC. Genome wide association study of fetal hemoglobin in sickle cell anemia in Tanzania. PLoS One 9:e111464, 2014.
  97. 97. Xu J, Bauer DE, Kerenyi MA, Vo TD, Hou S, Hsu YJ, Yao H, Trowbridge JJ, Mandel G, Orkin SH. Corepressor-dependent silencing of fetal hemoglobin expression by BCL11A. Proc Natl Acad Sci 110:6518–23, 2013.
  98. 98. Roosjen M, McColl B, Kao B, Gearing LJ, Blewitt ME, Vadolas J. Transcriptional regulators Myb and BCL11A interplay with DNA methyltransferase 1 in developmental silencing of embryonic and fetal β-like globin genes. FASEB J 28:1610–20, 2014.
  99. 99. Amaya M, Desai M, Gnanapragasam MN, Wang SZ, Zu Zhu S, Williams DC Jr, Ginder GD. Mi2β-mediated silencing of the fetal γ-globin gene in adult erythroid cells. Blood 121:3493–501, 2013.
  100. 100. Xu J, Sankaran VG, Ni M, Menne TF, Puram RV, Kim W, Orkin SH. Transcriptional silencing of γ-globin by BCL11A involves long-range interactions and cooperation with SOX6. Genes Dev 24:783–98, 2010.
  101. 101. Sankaran VG, Xu J, Byron R, Greisman HA, Fisher C, Weatherall DJ, Sabath DE, Groudine M, Orkin SH, Premawardhena A, Bender MA. A functional element necessary for fetal hemoglobin silencing. N Engl J Med 365:807–14, 2011.
  102. 102. Chen Z, Luo HY, Steinberg MH, Chui DH. BCL11A represses HBG transcription in K562 cells. Blood Cells Mol Dis 42:144–9, 2009.
  103. 103. Bauer DE, Kamran SC, Lessard S, Xu J, Fujiwara Y, Lin C, Shao Z, Canver MC, Smith EC, Pinello L, Sabo PJ, Vierstra J, Voit RA, Yuan GC, Porteus MH, Stamatoyannopoulos JA, Lettre G, Orkin SH. An erythroid enhancer of BCL11A subject to genetic variation determines fetal hemoglobin level. Science 342:253–7, 2013.
  104. 104. Menzel S, Rooks H, Zelenika D, Mtatiro SN, Gnanakulasekaran A, Drasar E, Cox S, Liu L, Masood M, Silver N, Garner C, Vasavda N, Howard J, Makani J, Adekile A, Pace B, Spector T, Farrall M, Lathrop M, Thein SL. Global genetic architecture of an erythroid quantitative trait locus, HMIP-2. Ann Hum Genet 78:434–51, 2014.
  105. 105. Ma Q, Wyszynski DF, Farrell JJ, Kutlar A, Farrer LA, Baldwin CT, Steinberg MH. Fetal hemoglobin in sickle cell anemia: genetic determinants of response to hydroxyurea. Pharmacogenomics J 7:386–94, 2007.
  106. 106. Chang YP, Maier-Redelsperger M, Smith KD, Contu L, Ducroco R, de Montalembert M, Belloy M, Elion J, Dover GJ, Girot R. The relative importance of the X-linked FCP locus and beta-globin haplotypes in determining haemoglobin F levels: a study of SS patients homozygous for beta S haplotypes. Br J Haematol 96:806–14, 1997.
  107. 107. Creary LE, Ulug P, Menzel S, McKenzie CA, Hanchard NA, Taylor V, Farall M, Forrester TE, Thein SL. Genetic variation on chromosome 6 influences F cell levels in healthy individuals of African descent and HbF levels in sickle cell patients. PLoS One 4:e4218, 2009.
  108. 108. Ware RE, Despotovic JM, Mortier NA, Flanagan JM, He J, Smeltzer MP, Kinble AC, Aygun B, Wu S, Joward T, Sparrebom A. Pharmacokinetics, pharmacodynamics, and pharmacogenetics of hydroxyurea treatment for children with sickle cell anemia. Blood 118:4985–91, 2011.
  109. 109. Bhatnagar P, Purvis S, Barron-Casella E, et al. Genome-wide association study identifies genetic variants influencing F-cell levels in sickle-cell patients. J Hum Genet 56:316–23, 2011.
  110. 110. Galarneau G, Palmer CD, Sankaran VG, Orkin SH, Hirschhorn JN, Lettre G. Fine-mapping at three loci known to affect fetal hemoglobin levels explains additional genetic variation. Nat Genet 42:1049–51, 2010.
  111. 111. Kumkhaek C, Taylor JG 6th, Zhu J, Hoppe C, Kato GJ, Rodgers GP. Fetal haemoglobin response to hydroxycarbamide treatment and sar1a promoter polymorphisms in sickle cell anaemia. Br J Haematol 141:254–9, 2008.
  112. 112. Lee YT, de Vasconcellos JF, Yuan J, Byrnes C, Noh SJ, Meier ER, Kim KS, Rabel A, Kaushal M, Muljo SA, Miller JL. LIN28B-mediated expression of fetal hemoglobin and production of fetal-like erythrocytes from adult human erythroblasts ex vivo. Blood 122:1034–41, 2013.
  113. 113. Sankaran VG, Menne TF, Scepanovic D, Vergilio JA, Ji P, Kim J, Thiru P, Orkin SH, Lander ES, Lodish HF. MicroRNA-15a and -16-1 act via MYB to elevate fetal hemoglobin expression in human trisomy 13. Proc Natl Acad Sci 108:1519–24, 2011.
  114. 114. Walker AL, Steward S, Howard TA, Mortier N, Smeltzer M, Wang YD, Ware RE. Epigenetic and molecular profiles of erythroid cells after HU treatment in sickle cell anemia. Blood 118:5664–70, 2011.
  115. 115. Azzouzi I, Moest H, Winkler J, Fauchere JC, Gerber AP, Wollscheid B, Stoffel M, Schmugge M, Speer O. MicroRNA-96 directly inhibits gamma-globin expression in human erythropoiesis. PLoS One 6:28, 2011.
  116. 116. Bianchi N, Zuccato C, Lampronti I, Borgatti M, Gambari R. Expression of miR-210 during erythroid differentiation and induction of gamma-globin gene expression. BMB Rep 42:493–9, 2009.
  117. 117. Ward CM, Li B, Pace BS. Stable expression of miR-34a mediates fetal hemoglobin induction in K562 cells. Exp Biol Med (Maywood) 241:719–29, 2016.
  118. 118. Lulli V, Romania P, Morsilli O, Cianciulli P, Gabbianelli M, Testa U, Giuliani A, Marziali G. MicroRNA-486-3p regulates gamma-globin expression in human erythroid cells by directly modulating BCL11A. PLoS One 8, 2013.
  119. 119. Xu J, Peng C, Sankaran VG, Shao Z, Esrick EB, Chong BG, Ippolito GC, Fujiwara Y, Ebert BL, Tucker PW, Orkin SH. Correction of sickle cell disease in adult mice by interference with fetal hemoglobin silencing. Science 334:993–6, 2011.
  120. 120. Borg J, Papadopoulos P, Georgitsi M, Gutiérrez L, Grech G, Fanis P, Phylactides M, Verkerk AJ, van der Spek PJ, Scerri CA, Cassar W, Galdies R, van Ijcken W, Ozgür Z, Gillemans N, Hou J, Bugeja M, Grosveld FG, von Lindern M, Felice AE, Patrinos GP, Philipsen S. Haploinsufficiency for the erythroid transcription factor KLF1 causes hereditary persistence of fetal hemoglobin. Nat Genet 42:801–5, 2010.
  121. 121. Zhou D, Liu K, Sun CW, Pawlik KM, Townes TM. KLF1 regulates BCL11A expression and gamma- to beta-globin gene switching. Nat Genet 42:742–4, 2010.

Written By

Betty S. Pace, Nicole H. Lopez, Xingguo Zhu and Biaoru Li

Reviewed: 06 July 2016 Published: 10 November 2016