A replication study of novel fetal hemoglobin-associated genetic variants in sickle cell disease-only cohorts
Bibliographic record
Abstract
Sickle cell disease (SCD) is the most common monogenic disease in the world and is caused by mutations in the β-globin gene (HBB). Notably, SCD is characterized by extreme clinical heterogeneity. Inter-individual variation in fetal hemoglobin (HbF) levels strongly contributes to this patient-to-patient variability, with high HbF levels associated with decreased morbidity and mortality. Genetic association studies have identified and replicated HbF levels-associated variants at three loci: BCL11A, HBS1L-MYB, and HBB. In SCD patients, genetic variation at these three loci accounts for ~ 50% of HbF heritability. Genome-wide association studies (GWAS) in non-anemic and SCD patients of multiple ancestries have identified 20 new HbF-associated variants. However, these genetic associations have yet to be replicated in independent SCD cohorts. Here, we validated the association between HbF levels and variants at five of these new loci (ASB3, BACH2, PFAS, ZBTB7A, and KLF1) in up to 3740 SCD patients. By combining CRISPR inhibition and single-cell transcriptomics, we also showed that sequences near non-coding genetic variants at BACH2 (rs4707609) and KLF1 (rs2242514, rs10404876) can control the production of the β-globin genes in erythroid HUDEP-2 cells. Finally, we analyzed whole-exome sequence data from 1354 SCD patients but could not identify rare genetic variants of large effect on HbF levels. Together, our results confirm five new HbF-associated loci that can be functionally studied to develop new strategies to induce HbF expression in SCD patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".