Genetic determinants of haemolysis in sickle cell anaemia.

Haemolytic anaemia is variable among patients with sickle cell anaemia and can be estimated by reticulocyte count, lactate dehydrogenase, aspartate aminotransferase and bilirubin levels. Using principal component analysis of these measurements we computed a haemolytic score that we used as a subphenotype in a genome-wide association study. We identified in one cohort and replicated in two additional cohorts the association of a single nucleotide polymorphism in NPRL3 (rs7203560; chr16p13·3) (P = 6·04 × 10(-07) ). This association was validated by targeted genotyping in a fourth independent cohort. The HBA1/HBA2 regulatory elements, hypersensitive sites (HS)-33, HS-40 and HS-48 are located in introns of NPRL3. Rs7203560 was in perfect linkage disequilibrium (LD) with rs9926112 (r(2)  = 1) and in strong LD with rs7197554 (r(2)  = 0·75) and rs13336641 (r(2)  = 0·77); the latter is located between HS-33 and HS-40 sites and next to a CTCF binding site. The minor allele for rs7203560 was associated with the -∝(3·7) thalassaemia gene deletion. When adjusting for HbF and ∝ thalassaemia, the association of NPRL3 with the haemolytic score was significant (P = 0·00375) and remained significant when examining only cases without gene deletion∝ thalassaemia (P = 0·02463). Perhaps by independently down-regulating expression of the HBA1/HBA2 genes, variants of the HBA1/HBA2 gene regulatory loci, tagged by rs7203560, reduce haemolysis in sickle cell anaemia.

Fetal hemoglobin in sickle cell anemia: genome-wide association studies suggest a regulatory region in the 5' olfactory receptor gene cluster.

In a genome-wide association study of 848 blacks with sickle cell anemia, we identified single nucleotide polymorphisms (SNPs) associated with fetal hemoglobin concentration. The most significant SNPs in a discovery sample were tested in a replication set of 305 blacks with sickle cell anemia and in subjects with hemoglobin E or beta thalassemia trait from Thailand and Hong Kong. A novel region on chromosome 11 containing olfactory receptor genes OR51B5 and OR51B6 was identified by 6 SNPs (lowest P = 4.7E-08) and validated in the replication set. An additional olfactory receptor gene, OR51B2, was identified by a novel SNP set enrichment analysis. Genome-wide association studies also validated a previously identified SNP (rs766432) in BCL11A, a gene known to affect fetal hemoglobin levels (P = 2.6E-21) and in Thailand and Hong Kong subjects. Elements within the olfactory receptor gene cluster might play a regulatory role in gamma-globin gene expression.

Severe sickle cell anemia is associated with increased plasma levels of TNF-R1 and VCAM-1.

Sickle cell anemia (SCA, HBB glu6val) is characterized by multiple complications and a high degree of phenotypic variability: some subjects have only sporadic pain crises and few acute hospitalizations, while others experience multiple serious complications, high levels of morbidity, and accelerated mortality [1]. The tumor necrosis factor-α (TNF-α) signaling pathway plays important roles in inflammation and the immune response; variation in this pathway might be expected to modify the overall severity of SCA through the pathway's effects on the vascular endothelium [2,3]. We examined plasma biomarkers of TNF-α activity and endothelial cell activation for associations with SCA severity in 24 adults (12 mild, 12 severe). Two biomarkers, tumor necrosis factor-α receptor-1 (TNF-R1) and vascular cell adhesion molecule-1 (VCAM-1) were significantly higher in subjects with severe SCA. Along with these biomarker differences, we also examined data from a genome-wide association study (GWAS) using SCA severity as a disease phenotype, and found evidence of genetic association between disease severity and a single nucleotide polymorphism (SNP) in VCAM1, which codes for VCAM-1, and several SNPs in ARFGEF2, a gene involved in TNF-R1 release [4].

Genetic modifiers of the severity of sickle cell anemia identified through a genome-wide association study.

We conducted a genome-wide association study (GWAS) to discover single nucleotide polymorphisms (SNPs) associated with the severity of sickle cell anemia in 1,265 patients with either "severe" or "mild" disease based on a network model of disease severity. We analyzed data using single SNP analysis and a novel SNP set enrichment analysis (SSEA) developed to discover clusters of associated SNPs. Single SNP analysis discovered 40 SNPs that were strongly associated with sickle cell severity (odds for association >1,000); of the 32 that we could analyze in an independent set of 163 patients, five replicated, eight showed consistent effects although failed to reach statistical significance, whereas 19 did not show any convincing association. Among the replicated associations are SNPs in KCNK6 a K(+) channel gene. SSEA identified 27 genes with a strong enrichment of significant SNPs (P < 10(-6)); 20 were replicated with varying degrees of confidence. Among the novel findings identified by SSEA is the telomere length regulator gene TNKS. These studies are the first to use GWAS to understand the genetic diversity that accounts the phenotypic heterogeneity sickle cell anemia as estimated by an integrated model of severity. Additional validation, resequencing, and functional studies to understand the biology and reveal mechanisms by which candidate genes might have their effects are the future goals of this work.

Ear biometrics for patient identification in global health: a cross-sectional study to test the feasibility of a simplified algorithm.

BACKGROUND: One of the greatest public health challenges in low- and middle-income countries (LMICs) is identifying people over time and space. Recent years have seen an explosion of interest in developing electronic approaches to addressing this problem, with mobile technology at the forefront of these efforts. We investigate the possibility of biometrics as a simple, cost-efficient, and portable solution. Common biometrics approaches include fingerprinting, iris scanning and facial recognition, but all are less than ideal due to complexity, infringement on privacy, cost, or portability. Ear biometrics, however, proved to be a unique and viable solution. METHODS: We developed an identification algorithm then conducted a cross sectional study in which we photographed left and right ears from 25 consenting adults. We then conducted re-identification and statistical analyses to identify the accuracy and replicability of our approach. RESULTS: Through principal component analysis, we found the curve of the ear helix to be the most reliable anatomical structure and the basis for re-identification. Although an individual ear allowed for high re-identification rate (88.3%), when both left and right ears were paired together, our rate of re-identification amidst the pool of potential matches was 100%. CONCLUSIONS: The results of this study have implications on future efforts towards building a biometrics solution for patient identification in LMICs. We provide a conceptual platform for further investigation into the development of an ear biometrics identification mobile application.

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

Prediction of fetal hemoglobin in sickle cell anemia using an ensemble of genetic risk prediction models.

BACKGROUND: Fetal hemoglobin (HbF) is the major modifier of the clinical course of sickle cell anemia. Its levels are highly heritable, and its interpersonal variability is modulated in part by 3 quantitative trait loci that affect HbF gene expression. Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) in these quantitative trait loci that are highly associated with HbF but explain only 10% to 12% of the variance of HbF. Combining SNPs into a genetic risk score can help to explain a larger amount of the variability of HbF level, but the challenge of this approach is to select the optimal number of SNPs to be included in the genetic risk score. METHODS AND RESULTS: We developed a collection of 14 models with genetic risk score composed of different numbers of SNPs and used the ensemble of these models to predict HbF in patients with sickle cell anemia. The models were trained in 841 patients with sickle cell anemia and were tested in 3 independent cohorts. The ensemble of 14 models explained 23.4% of the variability in HbF in the discovery cohort, whereas the correlation between predicted and observed HbF in the 3 independent cohorts ranged between 0.28 and 0.44. The models included SNPs in BCL11A, the HBS1L-MYB intergenic region, and the site of the HBB gene cluster, quantitative trait loci previously associated with HbF. CONCLUSIONS: An ensemble of 14 genetic risk models can predict HbF levels with accuracy between 0.28 and 0.44, and the approach may also prove useful in other applications.

Rare genetic variant analysis on blood pressure in related samples.

The genetic variants associated with blood pressure identified so far explain only a small proportion of the total heritability of this trait. With recent advances in sequencing technology and statistical methodology, it becomes feasible to study the association between blood pressure and rare genetic variants. Using real baseline phenotype data and imputed dosage data from Genetic Analysis Workshop 18, we performed a candidate gene association analysis. We focused on 8 genes shown to be associated with either systolic or diastolic blood pressure to identify the association with both common and rare genetic variants, and then did a genome-wide rare-variant analysis on blood pressure. We performed association analysis for rare coding and splicing variants within each gene region and all rare variants in each sliding window, using either burden tests or sequence kernel association tests accounting for familial correlation. With a sample size of only 747, we failed to find any novel associated genetic loci. Consequently, we performed analyses on simulated data, with knowledge of the underlying simulating model, to evaluate the type I error rate and power for the methods used in real data analysis.

Genome-wide meta-analysis of systolic blood pressure in children with sickle cell disease.

In pediatric sickle cell disease (SCD) patients, it has been reported that higher systolic blood pressure (SBP) is associated with increased risk of a silent cerebral infarction (SCI). SCI is a major cause of neurologic morbidity in children with SCD, and blood pressure is a potential modulator of clinical manifestations of SCD; however, the risk factors underlying these complications are not well characterized. The aim of this study was to identify genetic variants that influence SBP in an African American population in the setting of SCD, and explore the use of SBP as an endo-phenotype for SCI. We conducted a genome-wide meta-analysis for SBP using two SCD cohorts, as well as a candidate screen based on published SBP loci. A total of 1,617 patients were analyzed, and while no SNP reached genome-wide significance (P-value<5.0 x 10(-8)), a number of suggestive candidate loci were identified. The most significant SNP, rs7952106 (P-value=8.57 x 10(-7)), was in the DRD2 locus on chromosome 11. In a gene-based association analysis, MIR4301 (micro-RNA4301), which resides in an intron of DRD2, was the most significant gene (P-value=5.2 x 10(-5)). Examining 27 of the previously reported SBP associated SNPs, 4 SNPs were nominally significant. A genetic risk score was constructed to assess the aggregated genetic effect of the published SBP variants, demonstrating a significant association (P=0.05). In addition, we also assessed whether these variants are associated with SCI, validating the use of SBP as an endo-phenotype for SCI. Three SNPs were nominally associated, and only rs2357790 (5' CACNB2) was significant for both SBP and SCI. None of these SNPs retained significance after Bonferroni correction. Taken together, our results suggest the importance of DRD2 genetic variation in the modulation of SBP, and extend the aggregated importance of previously reported SNPs in the modulation of SBP in an African American cohort, more specifically in children with SCD.

A genome-wide association study of total bilirubin and cholelithiasis risk in sickle cell anemia.

Serum bilirubin levels have been associated with polymorphisms in the UGT1A1 promoter in normal populations and in patients with hemolytic anemias, including sickle cell anemia. When hemolysis occurs circulating heme increases, leading to elevated bilirubin levels and an increased incidence of cholelithiasis. We performed the first genome-wide association study (GWAS) of bilirubin levels and cholelithiasis risk in a discovery cohort of 1,117 sickle cell anemia patients. We found 15 single nucleotide polymorphisms (SNPs) associated with total bilirubin levels at the genome-wide significance level (p value <5 × 10(-8)). SNPs in UGT1A1, UGT1A3, UGT1A6, UGT1A8 and UGT1A10, different isoforms within the UGT1A locus, were identified (most significant rs887829, p = 9.08 × 10(-25)). All of these associations were validated in 4 independent sets of sickle cell anemia patients. We tested the association of the 15 SNPs with cholelithiasis in the discovery cohort and found a significant association (most significant p value 1.15 × 10(-4)). These results confirm that the UGT1A region is the major regulator of bilirubin metabolism in African Americans with sickle cell anemia, similar to what is observed in other ethnicities.

Whole genome sequences of a male and female supercentenarian, ages greater than 114 years.

Supercentenarians (age 110+ years old) generally delay or escape age-related diseases and disability well beyond the age of 100 and this exceptional survival is likely to be influenced by a genetic predisposition that includes both common and rare genetic variants. In this report, we describe the complete genomic sequences of male and female supercentenarians, both age >114 years old. We show that: (1) the sequence variant spectrum of these two individuals' DNA sequences is largely comparable to existing non-supercentenarian genomes; (2) the two individuals do not appear to carry most of the well-established human longevity enabling variants already reported in the literature; (3) they have a comparable number of known disease-associated variants relative to most human genomes sequenced to-date; (4) approximately 1% of the variants these individuals possess are novel and may point to new genes involved in exceptional longevity; and (5) both individuals are enriched for coding variants near longevity-associated variants that we discovered through a large genome-wide association study. These analyses suggest that there are both common and rare longevity-associated variants that may counter the effects of disease-predisposing variants and extend lifespan. The continued analysis of the genomes of these and other rare individuals who have survived to extremely old ages should provide insight into the processes that contribute to the maintenance of health during extreme aging.