A genome-wide association identified the common genetic variants influence disease severity in β0-thalassemia/hemoglobin E
TL;DR: It is revealed that all the three reported loci and the α-globin gene locus are the best and common predictors of the disease severity in β-thalassemia.
Abstract: β-Thalassemia/HbE disease is clinically variable. In searching for genetic factors modifying the disease severity, patients were selected based on their disease severities, and a genome-wide association study (GWAS) was performed. Genotyping was conducted with the Illumina Human 610-Quad BeadChips array using DNAs from 618 Thai β0-thalassemia/HbE patients who were classified as 383 severe and 235 mild phenotypes by a validated scoring system. Twenty-three SNPs in three independent genes/regions were identified as being significantly associated with the disease severity. The highest association was observed with SNPs in the β-globin gene cluster (chr.11p15), and rs2071348 of the HBBP1 gene revealed the most significant association [P = 2.96 × 10−13, odds ratio (OR) = 4.33 (95% confidence interval (CI), 2.74–6.84)]. The second was identified in the intergenic region between the HBS1L and MYB genes (chr.6q23), among which rs9376092 was the most significant [P = 2.36 × 10−10, OR = 3.07 (95% CI, 2.16–4.38)]. The third region was located in the BCL11A gene (chr.2p16.1), and rs766432 showed the most significant association [P = 5.87 × 10−10, OR = 3.06 (95% CI, 2.15–4.37)]. All three loci were replicated in an independent cohort of 174 Indonesian patients. The associations to fetal hemoglobin levels were also observed with SNPs on these three regions. Our data indicate that several genetic loci act in concert to influence HbF levels of β0-thalassemia/HbE patients. This study revealed that all the three reported loci and the α-globin gene locus are the best and common predictors of the disease severity in β-thalassemia.
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TL;DR: It is found that common genetic variation at BCL11A associated with fetal hemoglobin (HbF) level lies in noncoding sequences decorated by an erythroid enhancer chromatin signature, illustrating how GWASs may expose functional variants of modest impact within causal elements essential for appropriate gene expression.
Abstract: Genome-wide association studies (GWASs) have ascertained numerous trait-associated common genetic variants, frequently localized to regulatory DNA. We found that common genetic variation at BCL11A associated with fetal hemoglobin (HbF) level lies in noncoding sequences decorated by an erythroid enhancer chromatin signature. Fine-mapping uncovers a motif-disrupting common variant associated with reduced transcription factor (TF) binding, modestly diminished BCL11A expression, and elevated HbF. The surrounding sequences function in vivo as a developmental stage-specific, lineage-restricted enhancer. Genome engineering reveals the enhancer is required in erythroid but not B-lymphoid cells for BCL11A expression. These findings illustrate how GWASs may expose functional variants of modest impact within causal elements essential for appropriate gene expression. We propose the GWAS-marked BCL11A enhancer represents an attractive target for therapeutic genome engineering for the β-hemoglobinopathies.
543 citations
TL;DR: Natural human genetic variation is relied upon to identify effects of variants on trans-gene expression (expression quantitative trait locus mapping, eQTL) in whole peripheral blood from 1,469 unrelated individuals, supporting the concept that the effects of these SNPs on expression seems to be much less multifactorial.
Abstract: For many complex traits, genetic variants have been found associated. However, it is still mostly unclear through which downstream mechanism these variants cause these phenotypes. Knowledge of these intermediate steps is crucial to understand pathogenesis, while also providing leads for potential pharmacological intervention. Here we relied upon natural human genetic variation to identify effects of these variants on trans-gene expression (expression quantitative trait locus mapping, eQTL) in whole peripheral blood from 1,469 unrelated individuals. We looked at 1,167 published trait- or disease-associated SNPs and observed trans-eQTL effects on 113 different genes, of which we replicated 46 in monocytes of 1,490 different individuals and 18 in a smaller dataset that comprised subcutaneous adipose, visceral adipose, liver tissue, and muscle tissue. HLA single-nucleotide polymorphisms (SNPs) were 10-fold enriched for trans-eQTLs: 48% of the trans-acting SNPs map within the HLA, including ulcerative colitis susceptibility variants that affect plausible candidate genes AOAH and TRBV18 in trans. We identified 18 pairs of unlinked SNPs associated with the same phenotype and affecting expression of the same trans-gene (21 times more than expected, P<10(-16)). This was particularly pronounced for mean platelet volume (MPV): Two independent SNPs significantly affect the well-known blood coagulation genes GP9 and F13A1 but also C19orf33, SAMD14, VCL, and GNG11. Several of these SNPs have a substantially higher effect on the downstream trans-genes than on the eventual phenotypes, supporting the concept that the effects of these SNPs on expression seems to be much less multifactorial. Therefore, these trans-eQTLs could well represent some of the intermediate genes that connect genetic variants with their eventual complex phenotypic outcomes.
395 citations
Cites background from "A genome-wide association identifie..."
...levels [37–39] and ß thalassemia susceptibility [40], significantly affect hemoglobin gamma G (HBG2) gene expression levels (each with p,1....
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TL;DR: The SNPfold algorithm can help identify RiboSNitches by leveraging GWAS data and an analysis of the mRNA structural ensemble, and it is proposed that the UTR and SNP combinations the authors identify constitute a “RiboSNitch,” that is a regulatory RNA in which a specific SNP has a structural consequence that results in a disease phenotype.
Abstract: Genome-wide association studies (GWAS) often identify disease-associated mutations in intergenic and non-coding regions of the genome. Given the high percentage of the human genome that is transcribed, we postulate that for some observed associations the disease phenotype is caused by a structural rearrangement in a regulatory region of the RNA transcript. To identify such mutations, we have performed a genome-wide analysis of all known disease-associated Single Nucleotide Polymorphisms (SNPs) from the Human Gene Mutation Database (HGMD) that map to the untranslated regions (UTRs) of a gene. Rather than using minimum free energy approaches (e.g. mFold), we use a partition function calculation that takes into consideration the ensemble of possible RNA conformations for a given sequence. We identified in the human genome disease-associated SNPs that significantly alter the global conformation of the UTR to which they map. For six disease-states (Hyperferritinemia Cataract Syndrome, β-Thalassemia, Cartilage-Hair Hypoplasia, Retinoblastoma, Chronic Obstructive Pulmonary Disease (COPD), and Hypertension), we identified multiple SNPs in UTRs that alter the mRNA structural ensemble of the associated genes. Using a Boltzmann sampling procedure for sub-optimal RNA structures, we are able to characterize and visualize the nature of the conformational changes induced by the disease-associated mutations in the structural ensemble. We observe in several cases (specifically the 5′ UTRs of FTL and RB1) SNP–induced conformational changes analogous to those observed in bacterial regulatory Riboswitches when specific ligands bind. We propose that the UTR and SNP combinations we identify constitute a “RiboSNitch,” that is a regulatory RNA in which a specific SNP has a structural consequence that results in a disease phenotype. Our SNPfold algorithm can help identify RiboSNitches by leveraging GWAS data and an analysis of the mRNA structural ensemble.
289 citations
TL;DR: This work used resequencing and genotyping in African Americans with sickle cell anemia to characterize associations with fetal hemoglobin levels at the BCL11A, HBS1L-MYB and β-globin loci and confirmed seven SNPs with independent effects and increased the explained heritable variation in HbF levels.
Abstract: We used resequencing and genotyping in African Americans with sickle cell anemia (SCA) to characterize associations with fetal hemoglobin (HbF) levels at the BCL11A, HBS1L-MYB and β-globin loci. Fine-mapping of HbF association signals at these loci confirmed seven SNPs with independent effects and increased the explained heritable variation in HbF levels from 38.6% to 49.5%. We also identified rare missense variants that causally implicate MYB in HbF production.
251 citations
TL;DR: This article discusses historic attempts to induce HbF that have resulted in some therapeutic approaches to manage SCD and β-thalassemia, and chronologically covers the work accomplished as this field has evolved over the course of the past four decades.
Abstract: The fetal-to-adult hemoglobin switch and silencing of fetal hemoglobin (HbF) have been areas of long-standing interest among hematologists, given the fact that clinical induction of HbF production holds tremendous promise to ameliorate the clinical symptoms of sickle cell disease (SCD) and β-thalassemia. In this article, we discuss historic attempts to induce HbF that have resulted in some therapeutic approaches to manage SCD and β-thalassemia. We then go on to discuss how more recent molecular studies that have identified regulators, including BCL11A, MYB, and KLF1, hold great promise to develop targeted and more effective approaches for HbF induction. We go on to discuss strategies by which such approaches may be developed. Older studies in this field can provide important lessons for future studies aimed at developing more effective strategies for HbF induction, and we therefore chronologically cover the work accomplished as this field has evolved over the course of the past four decades.
248 citations
Cites background from "A genome-wide association identifie..."
...…which these variants result in alterations in HbF levels is important, as the genetic variants at this locus appear to have as great or perhaps even a greater effect on clinical morbidity in the b-hemoglobinopathies as those variants at the BCL11A locus (Galanello et al. 2009; Nuinoon et al. 2010)....
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...The additivity of the effects of variants in the HBS1L-MYB intergenic region along with variants at the BCL11A locus (Lettre et al. 2008; Galanello et al. 2009; Nuinoon et al. 2010) suggests that targeting both of these pathways together could yield even more robust effects than targeting either pathway alone....
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...…of the effects of variants in the HBS1L-MYB intergenic region along with variants at the BCL11A locus (Lettre et al. 2008; Galanello et al. 2009; Nuinoon et al. 2010) suggests that targeting both of these pathways together could yield even more robust effects than targeting either pathway alone....
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...Understanding the mechanism of action by which these variants result in alterations in HbF levels is important, as the genetic variants at this locus appear to have as great or perhaps even a greater effect on clinical morbidity in the b-hemoglobinopathies as those variants at the BCL11A locus (Galanello et al. 2009; Nuinoon et al. 2010)....
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...Larger epidemiological studies of thalassemia populations have confirmed such findings (Premawardhena et al. 2005; Galanello et al. 2009; Nuinoon et al. 2010)....
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References
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TL;DR: This work describes a method that enables explicit detection and correction of population stratification on a genome-wide scale and uses principal components analysis to explicitly model ancestry differences between cases and controls.
Abstract: Population stratification—allele frequency differences between cases and controls due to systematic ancestry differences—can cause spurious associations in disease studies. We describe a method that enables explicit detection and correction of population stratification on a genome-wide scale. Our method uses principal components analysis to explicitly model ancestry differences between cases and controls. The resulting correction is specific to a candidate marker’s variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. Our simple, efficient approach can easily be applied to disease studies with hundreds of thousands of markers. Population stratification—allele frequency differences between cases and controls due to systematic ancestry differences—can cause spurious associations in disease studies 1‐8 . Because the effects of stratification vary in proportion to the number of samples 9 , stratification will be an increasing problem in the large-scale association studies of the future, which will analyze thousands of samples in an effort to detect common genetic variants of weak effect. The two prevailing methods for dealing with stratification are genomic control and structured association 9‐14 . Although genomic control and structured association have proven useful in a variety of contexts, they have limitations. Genomic control corrects for stratification by adjusting association statistics at each marker by a uniform overall inflation factor. However, some markers differ in their allele frequencies across ancestral populations more than others. Thus, the uniform adjustment applied by genomic control may be insufficient at markers having unusually strong differentiation across ancestral populations and may be superfluous at markers devoid of such differentiation, leading to a loss in power. Structured association uses a program such as STRUCTURE 15 to assign the samples to discrete subpopulation clusters and then aggregates evidence of association within each cluster. If fractional membership in more than one cluster is allowed, the method cannot currently be applied to genome-wide association studies because of its intensive computational cost on large data sets. Furthermore, assignments of individuals to clusters are highly sensitive to the number of clusters, which is not well defined 14,16 .
9,387 citations
"A genome-wide association identifie..." refers background or methods in this paper
...The population stratification was determined by Eigen analysis using smartpca software and the estimation of inflation factor, k, for genomic control (Price et al. 2006)....
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...One sample was excluded from the analysis because the point exceed the six standard deviations of the mean in one of top ten principal components of EIGENSTRAT analysis (Price et al. 2006) (Supplementary Fig....
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...Statistical analysis The population stratification was determined by Eigen analysis using smartpca software and the estimation of inflation factor, k, for genomic control (Price et al. 2006)....
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TL;DR: A high-throughput 3C approach, 3C-Carbon Copy (5C), that employs microarrays or quantitative DNA sequencing using 454-technology as detection methods that should be widely applicable for large-scale mapping of cis- and trans- interaction networks of genomic elements and for the study of higher-order chromosome structure.
Abstract: Physical interactions between genetic elements located throughout the genome play important roles in gene regulation and can be identified with the Chromosome Conformation Capture (3C) methodology. 3C converts physical chromatin interactions into specific ligation products, which are quantified individually by PCR. Here we present a high-throughput 3C approach, 3C-Carbon Copy (5C), that employs microarrays or quantitative DNA sequencing using 454-technology as detection methods. We applied 5C to analyze a 400-kb region containing the human beta-globin locus and a 100-kb conserved gene desert region. We validated 5C by detection of several previously identified looping interactions in the beta-globin locus. We also identified a new looping interaction in K562 cells between the beta-globin Locus Control Region and the gamma-beta-globin intergenic region. Interestingly, this region has been implicated in the control of developmental globin gene switching. 5C should be widely applicable for large-scale mapping of cis- and trans- interaction networks of genomic elements and for the study of higher-order chromosome structure.
1,178 citations
"A genome-wide association identifie..." refers background or methods in this paper
...Linkage disequilibrium (LD) analysis revealed a large LD block spanning over 62-kb from the locus control region (LCR) of the b-globin gene cluster to the HBD gene (Supplementary Fig....
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...By means of 5C (chromosome conformation capture carbon copy), it was determined that this region forms a looping interaction in K562 cells with the b-globin locus control region (LCR) (Dostie et al. 2006)....
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...This large LD block includes the LCR, four functional b-globin-like genes (HBE1, HBG2, HBG1, and HBD) and one pseudogene (HBBP1)....
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...The 5C analysis also revealed physical interactions between the b-globin cluster LCR and the region located 50–100 kb upstream (Dostie et al. 2006)....
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TL;DR: BCL11A emerges as a therapeutic target for reactivation of HbF in β-hemoglobin disorders and occupies several discrete sites in the β-globin gene cluster, consistent with a direct role of BCL 11A in globin gene regulation.
Abstract: Differences in the amount of fetal hemoglobin (HbF) that persists into adulthood affect the severity of sickle cell disease and the beta-thalassemia syndromes. Genetic association studies have identified sequence variants in the gene BCL11A that influence HbF levels. Here, we examine BCL11A as a potential regulator of HbF expression. The high-HbF BCL11A genotype is associated with reduced BCL11A expression. Moreover, abundant expression of full-length forms of BCL11A is developmentally restricted to adult erythroid cells. Down-regulation of BCL11A expression in primary adult erythroid cells leads to robust HbF expression. Consistent with a direct role of BCL11A in globin gene regulation, we find that BCL11A occupies several discrete sites in the beta-globin gene cluster. BCL11A emerges as a therapeutic target for reactivation of HbF in beta-hemoglobin disorders.
794 citations
"A genome-wide association identifie..." refers background in this paper
...The expression of BCL11A in several isoforms is developmentally regulated, and it consequently affects HbF expression (Sankaran et al. 2008)....
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TL;DR: Genotyping additional BCL11A SNPs, HBS1L-MYB SNPs and an SNP upstream of Gγ-globin (HBG2; the XmnI polymorphism) provided a clear example of inherited common sequence variants modifying the severity of a monogenic disease.
Abstract: Sickle cell disease (SCD) is a debilitating monogenic blood disorder with a highly variable phenotype characterized by severe pain crises, acute clinical events, and early mortality. Interindividual variation in fetal hemoglobin (HbF) expression is a known and potentially heritable modifier of SCD severity. High HbF levels are correlated with reduced morbidity and mortality. Common single nucleotide polymorphisms (SNPs) at the BCL11A and HBS1L-MYB loci have been implicated previously in HbF level variation in nonanemic European populations. We recently demonstrated an association between a BCL11A SNP and HbF levels in one SCD cohort [Uda M, et al. (2008) Proc Natl Acad Sci USA 105:1620-1625]. Here, we genotyped additional BCL11A SNPs, HBS1L-MYB SNPs, and an SNP upstream of (G)gamma-globin (HBG2; the XmnI polymorphism), in two independent SCD cohorts: the African American Cooperative Study of Sickle Cell Disease (CSSCD) and an SCD cohort from Brazil. We studied the effect of these SNPs on HbF levels and on a measure of SCD-related morbidity (pain crisis rate). We strongly replicated the association between these SNPs and HbF level variation (in the CSSCD, P values range from 0.04 to 2 x 10(-42)). Together, common SNPs at the BCL11A, HBS1L-MYB, and beta-globin (HBB) loci account for >20% of the variation in HbF levels in SCD patients. We also have shown that HbF-associated SNPs associate with pain crisis rate in SCD patients. These results provide a clear example of inherited common sequence variants modifying the severity of a monogenic disease.
537 citations
"A genome-wide association identifie..." refers background or result in this paper
...In the third region, rs766432 within intron 2 of the BCL11A gene is located in the same LD block as rs4671393, which was previously reported as the most significantly associated SNP with HbF levels (Lettre et al. 2008; Menzel et al. 2007a)....
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...From the HapMap data, this SNP is in strong linkage disequilibrium with a previously reported SNPs (rs4895441) that showed significant association with HbF levels (Lettre et al. 2008) (Supplementary Fig....
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...located in the same LD block as rs4671393, which was previously reported as the most significantly associated SNP with HbF levels (Lettre et al. 2008; Menzel et al. 2007a)....
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TL;DR: A genome-wide association mapping strategy is applied to individuals with contrasting extreme trait values and a new F cell quantitative trait locus is mapped to BCL11A, which encodes a zinc-finger protein, on chromosome 2p15.
Abstract: F cells measure the presence of fetal hemoglobin, a heritable quantitative trait in adults that accounts for substantial phenotypic diversity of sickle cell disease and beta thalassemia. We applied a genome-wide association mapping strategy to individuals with contrasting extreme trait values and mapped a new F cell quantitative trait locus to BCL11A, which encodes a zinc-finger protein, on chromosome 2p15. The 2p15 BCL11A quantitative trait locus accounts for 15.1% of the trait variance.
492 citations
"A genome-wide association identifie..." refers background in this paper
...In the third region, rs766432 within intron 2 of the BCL11A gene is located in the same LD block as rs4671393, which was previously reported as the most significantly associated SNP with HbF levels (Lettre et al. 2008; Menzel et al. 2007a)....
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...The HMIP affected its association not only with the HbF levels but also with the cell numbers of platelet and monocyte in the peripheral blood (Menzel et al. 2007b)....
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...In our study, these three loci contributed to HbF levels at about 27% in Thai and at 14% in Indonesian patients whereas at nearly 44% in healthy European twin cohort (Menzel et al. 2007a)....
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