Assessment of Left Lung Remodeling With Magnetic Resonance Imaging in a Murine Model Following Exposure to Douglas Fir Smoke.

Wildland firefighters (WLFFs) experience lung function decline due to occupational exposure to fire smoke. WLFFs typically do not wear respiratory personal protective equipment, and if they do, it is a simple bandana, which is not effective at filtering smoke. To pinpoint the biological underpinnings of abnormal respiratory function following 3-7 years of WLFF service, we exposed mice to Douglas fir smoke (DFS) over 8 weeks. Following exposure, we assessed changes in lung structure through Magnetic Resonance Imaging (MRI) and histological analysis, which was supported by immunohistochemistry staining. With MRI, we found that the signal decay time, T2*, from ultrashort echo time (UTE) images was significantly shorter in mice exposed to DFS compared to air controls. In addition, the variation in T2* was more heterogeneously distributed throughout the left lung in DFS-exposed mice, compared to air controls. As confirmed by histological analysis, shorter T2* was caused by larger parenchyma airspace sizes and not fibrotic remodeling. Destruction of the alveolar spaces was likely due to inflammation, as measured by an influx of CD68+ macrophages and destruction due to enhanced neutrophil elastase. In addition, measurements of airspace dimensions from histology were more heterogeneously distributed throughout the lung, corroborating the enhanced relative dispersion of T2*. Findings from this study suggest that the decline in lung function observed in WLFFs may be due to emphysema-like changes in the lung, which can be quantified with MRI.

ANNORE: genetic fine-mapping with functional annotation.

Genome-wide association studies (GWASs) have successfully identified loci of the human genome implicated in numerous complex traits. However, the limitations of this study design make it difficult to identify specific causal variants or biological mechanisms of association. We propose a novel method, AnnoRE, which uses GWAS summary statistics, local correlation structure among genotypes and functional annotation from external databases to prioritize the most plausible causal single-nucleotide polymorphisms (SNPs) in each trait-associated locus. Our proposed method improves upon previous fine-mapping approaches by estimating the effects of functional annotation from genome-wide summary statistics, allowing for the inclusion of many annotation categories. By implementing a multiple regression model with differential shrinkage via random effects, we avoid reductive assumptions on the number of causal SNPs per locus. Application of this method to a large GWAS meta-analysis of body mass index identified six loci with significant evidence in favor of one or more variants. In an additional 24 loci, one or two variants were strongly prioritized over others in the region. The use of functional annotation in genetic fine-mapping studies helps to distinguish between variants in high LD and to identify promising targets for follow-up studies.

Estimation of the generation interval using pairwise relative transmission probabilities.

The generation interval (the time between infection of primary and secondary cases) and its often used proxy, the serial interval (the time between symptom onset of primary and secondary cases) are critical parameters in understanding infectious disease dynamics. Because it is difficult to determine who infected whom, these important outbreak characteristics are not well understood for many diseases. We present a novel method for estimating transmission intervals using surveillance or outbreak investigation data that, unlike existing methods, does not require a contact tracing data or pathogen whole genome sequence data on all cases. We start with an expectation maximization algorithm and incorporate relative transmission probabilities with noise reduction. We use simulations to show that our method can accurately estimate the generation interval distribution for diseases with different reproductive numbers, generation intervals, and mutation rates. We then apply our method to routinely collected surveillance data from Massachusetts (2010-2016) to estimate the serial interval of tuberculosis in this setting.

Systems Approach to Integrating Preclinical Apolipoprotein E-Knockout Investigations Reveals Novel Etiologic Pathways and Master Atherosclerosis Network in Humans.

OBJECTIVE: Animal models of atherosclerosis are used extensively to interrogate molecular mechanisms in serial fashion. We tested whether a novel systems biology approach to integration of preclinical data identifies novel pathways and regulators in human disease. Approach and Results: Of 716 articles published in ATVB from 1995 to 2019 using the apolipoprotein E knockout mouse to study atherosclerosis, data were extracted from 360 unique studies in which a gene was experimentally perturbed to impact plaque size or composition and analyzed using Ingenuity Pathway Analysis software. TREM1 (triggering receptor expressed on myeloid cells) signaling and LXR/RXR (liver X receptor/retinoid X receptor) activation were identified as the top atherosclerosis-associated pathways in mice (both P<1.93×10-4, TREM1 implicated early and LXR/RXR in late atherogenesis). The top upstream regulatory network in mice (sc-58125, a COX2 inhibitor) linked 64.0% of the genes into a single network. The pathways and networks identified in mice were interrogated by testing for associations between the genetically predicted gene expression of each mouse pathway-identified human homolog with clinical atherosclerosis in a cohort of 88 660 human subjects. Homologous human pathways and networks were significantly enriched for gene-atherosclerosis associations (empirical P<0.01 for TREM1 and LXR/RXR pathways and COX2 network). This included 12(60.0%) TREM1 pathway genes, 15(53.6%) LXR/RXR pathway genes, and 67(49.3%) COX2 network genes. Mouse analyses predicted, and human study validated, the strong association of COX2 expression (PTGS2) with increased likelihood of atherosclerosis (odds ratio, 1.68 per SD of genetically predicted gene expression; P=1.07×10-6). CONCLUSIONS: PRESCIANT (Preclinical Science Integration and Translation) leverages published preclinical investigations to identify high-confidence pathways, networks, and regulators of human disease.

Slower Decline in Processing Speed Is Associated with Familial Longevity.

INTRODUCTION: Cross-sectional analyses have associated familial longevity with better cognitive function and lower risk of cognitive impairment in comparison with individuals without familial longevity. The extent to which long-lived families also demonstrate slower rates of cognitive aging (i.e., change in cognition over time) is unknown. This study examined longitudinally collected data among 2 generations of the Long Life Family Study (LLFS) to compare rates of cognitive change across relatives and spouse controls. METHODS: We analyzed change in 6 neuropsychological test scores collected approximately 8 years apart among LLFS family members (n = 3,972) versus spouse controls (n = 1,092) using a Bayesian hierarchical model that included age, years of follow-up, sex, education, generation, and field center and all possible pairwise interactions. RESULTS: At a mean age of 88 years at enrollment in the older generation and 60 years in the younger generation, LLFS family members performed better than their spouses on the Digit Symbol Substitution Test (DSST) and the Logical Memory test. At follow-up, family members in the younger generation also showed slower decline than spouses on the DSST, whereas rates of change of Digit Span, fluency, and memory were similar between the 2 groups. DISCUSSION/CONCLUSION: Individuals in families with longevity appear to have better cognitive performance than their spouses for cognitive processes including psychomotor processing, episodic memory, and retrieval. Additionally, they demonstrate longer cognitive health spans with a slower decline on a multifactorial test of processing speed, a task requiring the integration of processes including organized visual search, working and incidental memory, and graphomotor ability. Long-lived families may be a valuable cohort for studying resilience to cognitive aging.

A Genome-Wide Association Study of 2304 Extreme Longevity Cases Identifies Novel Longevity Variants.

We performed a genome-wide association study (GWAS) of human extreme longevity (EL), defined as surviving past the 99th survival percentile, by aggregating data from four centenarian studies. The combined data included 2304 EL cases and 5879 controls. The analysis identified a locus in CDKN2B-AS1 (rs6475609, p = 7.13 × 10-8) that almost reached genome-wide significance and four additional loci that were suggestively significant. Among these, a novel rare variant (rs145265196) on chromosome 11 had much higher longevity allele frequencies in cases of Ashkenazi Jewish and Southern Italian ancestry compared to cases of other European ancestries. We also correlated EL-associated SNPs with serum proteins to link our findings to potential biological mechanisms that may be related to EL and are under genetic regulation. The findings from the proteomic analyses suggested that longevity-promoting alleles of significant genetic variants either provided EL cases with more youthful molecular profiles compared to controls or provided some form of protection from other illnesses, such as Alzheimer's disease, and disease progressions.

Using Cure Models to Estimate the Serial Interval of Tuberculosis With Limited Follow-up.

Serial interval (SI), defined as the time between symptom onset in an infector and infectee pair, is commonly used to understand infectious diseases transmission. Slow progression to active disease, as well as the small percentage of individuals who will eventually develop active disease, complicate the estimation of the SI for tuberculosis (TB). In this paper, we showed via simulation studies that when there is credible information on the percentage of those who will develop TB disease following infection, a cure model, first introduced by Boag in 1949, should be used to estimate the SI for TB. This model includes a parameter in the likelihood function to account for the study population being composed of those who will have the event of interest and those who will never have the event. We estimated the SI for TB to be approximately 0.5 years for the United States and Canada (January 2002 to December 2006) and approximately 2.0 years for Brazil (March 2008 to June 2012), which might imply a higher occurrence of reinfection TB in a developing country like Brazil.

PopCluster: an algorithm to identify genetic variants with ethnicity-dependent effects.

MOTIVATION: Over the last decade, more diverse populations have been included in genome-wide association studies. If a genetic variant has a varying effect on a phenotype in different populations, genome-wide association studies applied to a dataset as a whole may not pinpoint such differences. It is especially important to be able to identify population-specific effects of genetic variants in studies that would eventually lead to development of diagnostic tests or drug discovery. RESULTS: In this paper, we propose PopCluster: an algorithm to automatically discover subsets of individuals in which the genetic effects of a variant are statistically different. PopCluster provides a simple framework to directly analyze genotype data without prior knowledge of subjects' ethnicities. PopCluster combines logistic regression modeling, principal component analysis, hierarchical clustering and a recursive bottom-up tree parsing procedure. The evaluation of PopCluster suggests that the algorithm has a stable low false positive rate (∼4%) and high true positive rate (>80%) in simulations with large differences in allele frequencies between cases and controls. Application of PopCluster to data from genetic studies of longevity discovers ethnicity-dependent heterogeneity in the association of rs3764814 (USP42) with the phenotype. AVAILABILITY AND IMPLEMENTATION: PopCluster was implemented using the R programming language, PLINK and Eigensoft software, and can be found at the following GitHub repository: https://github.com/gurinovich/PopCluster with instructions on its installation and usage. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Biomarker signatures of sickle cell disease severity.

Identifying sickle cell disease patients at high risk of complications could lead to personalized treatment and better prognosis but despite many advances prediction of the clinical course of these patients remains elusive. We propose a system-type approach to discover profiles of multiple, common biomarkers that correlate with morbidity and mortality in sickle cell disease. We used cluster analysis to discover 17 signatures of 17 common circulating biomarkers in 2320 participants of the Cooperative Study of Sickle Cell Disease, and evaluated the association of these signatures with risk for stroke, pain, leg ulceration, acute chest syndrome, avascular necrosis, seizure, death, and trend of fetal hemoglobin and hemolysis using longitudinally collected data. The analysis shows that some of the signatures are associated with reduced risk for complications, while others are associated with increased risk for complications. We also show that these signatures repeat in two more contemporary studies of sickle cell disease and correlate with recently discovered biomarkers of pulmonary vascular disease. With replication and further study, these biomarker signatures could become an important and affordable precision medicine tool to aid treatment and management of the disease.

A phased SNP-based classification of sickle cell anemia HBB haplotypes.

BACKGROUND: Sickle cell anemia causes severe complications and premature death. Five common ß-globin gene cluster haplotypes are each associated with characteristic fetal hemoglobin (HbF) levels. As HbF is the major modulator of disease severity, classifying patients according to haplotype is useful. The first method of haplotype classification used restriction fragment length polymorphisms (RFLPs) to detect single nucleotide polymorphisms (SNPs) in the ß-globin gene cluster. This is labor intensive, and error prone. METHODS: We used genome-wide SNP data imputed to the 1000 Genomes reference panel to obtain phased data distinguishing parental alleles. RESULTS: We successfully haplotyped 813 sickle cell anemia patients previously classified by RFLPs with a concordance >98%. Four SNPs (rs3834466, rs28440105, rs10128556, and rs968857) marking four different restriction enzyme sites unequivocally defined most haplotypes. We were able to assign a haplotype to 86% of samples that were either partially or misclassified using RFLPs. CONCLUSION: Phased data using only four SNPs allowed unequivocal assignment of a haplotype that was not always possible using a larger number of RFLPs. Given the availability of genome-wide SNP data, our method is rapid and does not require high computational resources.

Fetal hemoglobin in sickle cell anemia: a glass half full?

Fetal hemoglobin (HbF) modulates the phenotype of sickle cell anemia by inhibiting deoxy sickle hemoglobin (HbS) polymerization. The blood concentration of HbF, or the number of cells with detectable HbF (F-cells), does not measure the amount of HbF/F-cell. Even patients with high HbF can have severe disease because HbF is unevenly distributed among F-cells, and some cells might have insufficient concentrations to inhibit HbS polymerization. With mean HbF levels of 5%, 10%, 20%, and 30%, the distribution of HbF/F-cell can greatly vary, even if the mean is constant. For example, with 20% HbF, as few as 1% and as many as 24% of cells can have polymer-inhibiting, or protective, levels of HbF of ∼10 pg; with lower HbF, few or no protected cells can be present. Only when the total HbF concentration is near 30% is it possible for the number of protected cells to approach 70%. Rather than the total number of F-cells or the concentration of HbF in the hemolysate, HbF/F-cell and the proportion of F-cells that have enough HbF to thwart HbS polymerization is the most critical predictor of the likelihood of severe sickle cell disease.

A candidate transacting modulator of fetal hemoglobin gene expression in the Arab-Indian haplotype of sickle cell anemia.

Fetal hemoglobin (HbF) levels are higher in the Arab-Indian (AI) ß-globin gene haplotype of sickle cell anemia compared with African-origin haplotypes. To study genetic elements that effect HbF expression in the AI haplotype we completed whole genome sequencing in 14 Saudi AI haplotype sickle hemoglobin homozygotes-seven selected for low HbF (8.2% ± 1.3%) and seven selected for high HbF (23.5% ± 2.6%). An intronic single nucleotide polymorphism (SNP) in ANTXR1, an anthrax toxin receptor (chromosome 2p13), was associated with HbF. These results were replicated in two independent Saudi AI haplotype cohorts of 120 and 139 patients, but not in 76 Saudi Benin haplotype, 894 African origin haplotype and 44 AI haplotype patients of Indian origin, suggesting that this association is effective only in the Saudi AI haplotype background. ANTXR1 variants explained 10% of the HbF variability compared with 8% for BCL11A. These two genes had independent, additive effects on HbF and together explained about 15% of HbF variability in Saudi AI sickle cell anemia patients. ANTXR1 was expressed at mRNA and protein levels in erythroid progenitors derived from induced pluripotent stem cells (iPSCs) and CD34+ cells. As CD34+ cells matured and their HbF decreased ANTXR1 expression increased; as iPSCs differentiated and their HbF increased, ANTXR1 expression decreased. Along with elements in cis to the HbF genes, ANTXR1 contributes to the variation in HbF in Saudi AI haplotype sickle cell anemia and is the first gene in trans to HBB that is associated with HbF only in carriers of the Saudi AI haplotype. Am. J. Hematol. 91:1118-1122, 2016. © 2016 Wiley Periodicals, Inc.

Hypoxic response contributes to altered gene expression and precapillary pulmonary hypertension in patients with sickle cell disease.

BACKGROUND: We postulated that the hypoxic response in sickle cell disease (SCD) contributes to altered gene expression and pulmonary hypertension, a complication associated with early mortality. METHODS AND RESULTS: To identify genes regulated by the hypoxic response and not other effects of chronic anemia, we compared expression variation in peripheral blood mononuclear cells from 13 subjects with SCD with hemoglobin SS genotype and 15 subjects with Chuvash polycythemia (VHL(R200W) homozygotes with constitutive upregulation of hypoxia-inducible factors in the absence of anemia or hypoxia). At a 5% false discovery rate, 1040 genes exhibited >1.15-fold change in both conditions; 297 were upregulated and 743 downregulated including MAPK8 encoding a mitogen-activated protein kinase important for apoptosis, T-cell differentiation, and inflammatory responses. Association mapping with a focus on local regulatory polymorphisms in 61 patients with SCD identified expression quantitative trait loci for 103 of these hypoxia response genes. In a University of Illinois SCD cohort, the A allele of a MAPK8 expression quantitative trait locus, rs10857560, was associated with precapillary pulmonary hypertension defined as mean pulmonary artery pressure ≥25 mm Hg and pulmonary capillary wedge pressure ≤15 mm Hg at right heart catheterization (allele frequency, 0.66; odds ratio, 13.8; n=238). This association was confirmed in an independent Walk-Treatment of Pulmonary Hypertension and Sickle Cell Disease With Sildenafil Therapy cohort (allele frequency, 0.65; odds ratio, 11.3; n=519). The homozygous AA genotype of rs10857560 was associated with decreased MAPK8 expression and present in all 14 of the identified precapillary pulmonary hypertension cases among the combined 757 patients. CONCLUSIONS: Our study demonstrates a prominent hypoxic transcription component in SCD and a MAPK8 expression quantitative trait locus associated with precapillary pulmonary hypertension.

Genetic polymorphism of APOB is associated with diabetes mellitus in sickle cell disease.

Environmental variations have strong influences in the etiology of type 2 diabetes mellitus. In this study, we investigated the genetic basis of diabetes in patients with sickle cell disease (SCD), a Mendelian disorder accompanied by distinct physiological conditions of hypoxia and hyperactive erythropoiesis. Compared to the general African American population, the prevalence of diabetes as assessed in two SCD cohorts of 856 adults was low, but it markedly increased with older age and overweight. Meta-analyses of over 5 million single-nucleotide polymorphisms (SNPs) in the two SCD cohorts identified a SNP, rs59014890, the C allele of which associated with diabetes risk at P = 3.2 × 10(-8) and, surprisingly, associated with decreased APOB expression in peripheral blood mononuclear cells (PBMCs). The risk allele of the APOB polymorphism was associated with overweight in 181 SCD adolescents, with diabetes risk in 592 overweight, non-SCD African Americans ≥ 45 years of age, and with elevated plasma lipid concentrations in general populations. In addition, lower expression level of APOB in PBMCs was associated with higher values for percent hemoglobin A1C and serum total cholesterol and triglyceride concentrations in patients with Chuvash polycythemia, a congenital disease with elevated hypoxic responses and increased erythropoiesis at normoxia. Our study reveals a novel, environment-specific genetic polymorphism that may affect key metabolic pathways contributing to diabetes in SCD.

Temporal gene expression profiling of the rat knee joint capsule during immobilization-induced joint contractures.

BACKGROUND: Contractures of the knee joint cause disability and handicap. Recovering range of motion is recognized by arthritic patients as their preference for improved health outcome secondary only to pain management. Clinical and experimental studies provide evidence that the posterior knee capsule prevents the knee from achieving full extension. This study was undertaken to investigate the dynamic changes of the joint capsule transcriptome during the progression of knee joint contractures induced by immobilization. We performed a microarray analysis of genes expressed in the posterior knee joint capsule following induction of a flexion contracture by rigidly immobilizing the rat knee joint over a time-course of 16 weeks. Fold changes of expression values were measured and co-expressed genes were identified by clustering based on time-series analysis. Genes associated with immobilization were further analyzed to reveal pathways and biological significance and validated by immunohistochemistry on sagittal sections of knee joints. RESULTS: Changes in expression with a minimum of 1.5 fold changes were dominated by a decrease in expression for 7732 probe sets occurring at week 8 while the expression of 2251 probe sets increased. Clusters of genes with similar profiles of expression included a total of 162 genes displaying at least a 2 fold change compared to week 1. Functional analysis revealed ontology categories corresponding to triglyceride metabolism, extracellular matrix and muscle contraction. The altered expression of selected genes involved in the triglyceride biosynthesis pathway; AGPAT-9, and of the genes P4HB and HSP47, both involved in collagen synthesis, was confirmed by immunohistochemistry. CONCLUSIONS: Gene expression in the knee joint capsule was sensitive to joint immobility and provided insights into molecular mechanisms relevant to the pathophysiology of knee flexion contractures. Capsule responses to immobilization was dynamic and characterized by modulation of at least three reaction pathways; down regulation of triglyceride biosynthesis, alteration of extracellular matrix degradation and muscle contraction gene expression. The posterior knee capsule may deploy tissue-specific patterns of mRNA regulatory responses to immobilization. The identification of altered expression of genes and biochemical pathways in the joint capsule provides potential targets for the therapy of knee flexion contractures.

Prenatal buprenorphine versus methadone exposure and neonatal outcomes: systematic review and meta-analysis.

Increasing rates of maternal opioid use during pregnancy and neonatal withdrawal, termed neonatal abstinence syndrome (NAS), are public health concerns. Prenatal buprenorphine maintenance treatment (BMT) versus methadone maintenance treatment (MMT) may improve neonatal outcomes, but associations vary. To summarize evidence, we used a random-effects meta-analysis model and estimated summary measures of BMT versus MMT on several outcomes. Sensitivity analyses evaluated confounding, publication bias, and heterogeneity. Subjects were 515 neonates whose mothers received BMT and 855 neonates whose mothers received MMT and who were born from 1996 to 2012 and who were included in 12 studies. The unadjusted NAS treatment risk was lower (risk ratio=0.90, 95% confidence interval (CI): 0.81, 0.98) and mean length of hospital stay shorter (-7.23 days, 95% CI: -10.64, -3.83) in BMT-exposed versus MMT-exposed neonates. In treated neonates, NAS treatment duration was shorter (-8.46 days, 95% CI: -14.48, -2.44) and morphine dose lower (-3.60 mg, 95% CI: -7.26, 0.07) in those exposed to BMT. BMT-exposed neonates had higher mean gestational age and greater weight, length, and head circumference at birth. Fewer women treated with BMT used illicit opioids near delivery (risk ratio=0.44, 95% CI: 0.28, 0.70). Simulations suggested that confounding by indication could account for some of the observed differences. Prenatal BMT versus MMT may improve neonatal outcomes, but bias may contribute to this protective association. Further evidence is needed to guide treatment choices.

Sickle cell disease in Saudi Arabia: the phenotype in adults with the Arab-Indian haplotype is not benign.

Sickle cell disease (SCD) in Saudi patients from the Eastern Province is associated with the Arab-Indian (AI) HBB (ß-globin gene) haplotype. The phenotype of AI SCD in children was described as benign and was attributed to their high fetal haemoglobin (HbF). We conducted a hospital-based study to assess the pattern of SCD complications in adults. A total of 104 patients with average age of 27 years were enrolled. Ninety-six per cent of these patients reported history of painful crisis; 47% had at least one episode of acute chest syndrome, however, only 15% had two or more episodes; symptomatic osteonecrosis was reported in 18%; priapism in 17%; overt stroke in 6%; none had leg ulcers. The majority of patients had persistent splenomegaly and 66% had gallstones. Half of the patients co-inherited α-thalassaemia and about one-third had glucose-6-phosphate dehydrogenase deficiency. Higher HbF correlated with higher rate of splenic sequestration but not with other phenotypes. The phenotype of adult patients with AI SCD is not benign despite their relatively high HbF level. This is probably due to the continued decline in HbF level in adults and the heterocellular and variable distribution of HbF amongst F-cells.

PleioGRiP: genetic risk prediction with pleiotropy.

MOTIVATION: Although several studies have used Bayesian classifiers for risk prediction using genome-wide single nucleotide polymorphism (SNP) datasets, no software can efficiently perform these analyses on massive genetic datasets and can accommodate multiple traits. RESULTS: We describe the program PleioGRiP that performs a genome-wide Bayesian model search to identify SNPs associated with a discrete phenotype and uses SNPs ranked by Bayes factor to produce nested Bayesian classifiers. These classifiers can be used for genetic risk prediction, either selecting the classifier with optimal number of features or using an ensemble of classifiers. In addition, PleioGRiP implements an extension to the Bayesian search and classification and can search for pleiotropic relationships in which SNPs are simultaneously associated with two or more distinct phenotypes. These relationships can be used to generate connected Bayesian classifiers to predict the phenotype of interest either using genetic data alone or in combination with the secondary phenotype(s). AVAILABILITY: PleioGRiP is implemented in Java, and it is available from http://hdl.handle.net/2144/4367. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The genetics of hemoglobin A2 regulation in sickle cell anemia.

Hemoglobin A2 , a tetramer of α- and δ-globin chains, comprises less than 3% of total hemoglobin in normal adults. In northern Europeans, single nucleotide polymorphisms (SNPs) in the HBS1L-MYB locus on chromosome 6q and the HBB cluster on chromosome 11p were associated with HbA2 levels. We examined the genetic basis of HbA2 variability in sickle cell anemia using genome-wide association studies. HbA2 levels were associated with SNPs in the HBS1L-MYB interval and SNPs in BCL11A. These effects are mediated by the association of these loci with γ-globin gene expression and fetal hemoglobin (HbF) levels. The association of polymorphisms downstream of the ß-globin gene (HBB) cluster on chromosome 11 with HbA2 was not mediated by HbF. In sickle cell anemia, levels of HbA2 appear to be modulated by trans-acting genes that affect HBG expression and perhaps also elements within the ß-globin gene cluster. HbA2 is expressed pancellularly and can inhibit HbS polymerization. It remains to be seen if genetic regulators of HbA2 can be exploited for therapeutic purposes.