ArticleCirculation. Cardiovascular genetics2014
Prediction of fetal hemoglobin in sickle cell anemia using an ensemble of genetic risk prediction models.
Article in Circulation. Cardiovascular genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.
- Genetic Polymorphisms Associated with Fetal Hemoglobin (HbF) Levels and F-Cell Numbers: A Systematic Review of Genome-Wide Association Studies.International journal of molecular sciences · 2024Pooled it
- Genetic Variation and Sickle Cell Disease Severity: A Systematic Review and Meta-Analysis.JAMA network open · 2023Pooled it
- BCL11A and HBS1L-MYB polymorphisms, in association with hydroxyurea and sex, modulate fetal hemoglobin levels in individuals with sickle cell anemia in the western region of Bahia, Brazil.Molecular biology reports · 2026Article
- A genetic risk score based on BCL11A and HBS1L-MYB variants predicts clinical severity in Brazilian sickle cell anaemia patients.British journal of haematology · 2026Article
- Improving Pain Assessment Using Vital Signs and Pain Medication for Patients With Sickle Cell Disease: Retrospective Study.JMIR formative research · 2022Article
- Pain Intensity Assessment in Sickle Cell Disease Patients Using Vital Signs During Hospital Visits.Pattern Recognition : ICPR International Workshops and Challenges, virtual event, January 10-15, 2021, proceedings. Part I. International Conference on Pattern Recognition (25th : 2021 : Online) · 2021Article
- Use of Mobile Health Apps and Wearable Technology to Assess Changes and Predict Pain During Treatment of Acute Pain in Sickle Cell Disease: Feasibility Study.JMIR mHealth and uHealth · 2019Article
- Genetic Modifiers of Fetal Haemoglobin in Sickle Cell Disease.Molecular diagnosis & therapy · 2019Review
- Sickle cell disease in the era of precision medicine: looking to the future.Expert review of precision medicine and drug development · 2019Article
- Biomarker signatures of sickle cell disease severity.Blood cells, molecules & diseases · 2018Article
- Improving Pain Management in Patients with Sickle Cell Disease from Physiological Measures Using Machine Learning Techniques.Smart health (Amsterdam, Netherlands) · 2018Article
- Article
- Protective BCL11A and HBS1L-MYB polymorphisms in a cohort of 102 Congolese patients suffering from sickle cell anemia.Journal of clinical laboratory analysis · 2018Article
- A deep convolutional neural network for classification of red blood cells in sickle cell anemia.PLoS computational biology · 2017Article
- Original Research: A case-control genome-wide association study identifies genetic modifiers of fetal hemoglobin in sickle cell disease.Experimental biology and medicine (Maywood, N.J.) · 2016Article
- Genomic approaches to identifying targets for treating β hemoglobinopathies.BMC medical genomics · 2015Review
- Hashimoto's thyroiditis and acute chest syndrome revealing sickle cell anemia in a 32 years female patient.The Pan African medical journal · 2015Article
- The genetics of hemoglobin A2 regulation in sickle cell anemia.American journal of hematology · 2014Article
- Regularized machine learning in the genetic prediction of complex traits.PLoS genetics · 2014Article
- C-reactive Protein and Disease Outcome in Nigerian Sickle Cell Disease Patients.Annals of medical and health sciences research · 2014Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundFetal 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
resultsWe 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.
conclusionsAn 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.