Single-Cell Transcriptional Landscapes of Human Bone Marrow Reveal Distinct Erythroid Phenotypes Underpinned By Genotype in Diamond-Blackfan Anemia
Bibliographic record
Abstract
Background: Diamond- Blackfan Anemia (DBA) is a rare, heritable ribosomopathy caused by mutations in ribosomal protein large (RPL) and small (RPS) subunit genes. The diagnostic criteria of DBA include presentation in infancy with virtually no mature erythroblasts (EB) on bone marrow (BM) examination, however atypical presentations in later life with milder haematological manifestations are increasingly reported. The cellular and molecular mechanisms underpinning variable clinical phenotypes, and how they relate to genotype, are yet to be elucidated. Furthermore, as many DBA patients do not respond to corticosteroids, understanding the pathological processes contributing to erythroid failure is a prerequisite for developing novel, precision-medicine therapies. Aim: To elucidate phenotypic and functional differences in erythropoiesis in RPS- and RPL-DBA, using primary BM samples from patients. Methods: We performed single-cell transcriptome profiling (scRNAseq), using the 10X Genomics chromium platform, of 45,488 CD34+ Lineage negative (Lin-) BM hematopoietic stem and progenitor cells (HSPC), purified by fluorescence-activated cell sorting. We included six patients with red cell transfusion-dependent DBA (aged 2-19y) with mutations in RPS19 (n=3), RPL11 (n=1) and RPL5 (n=2) and three healthy donors (aged 3-17y). We validated our findings using bulk RNAseq, functional assays, and deep immunophenotyping-based dissection of the haematopoietic architecture of DBA BM ex vivo. Results: High quality sequencing data was obtained for all nine donors; after quality control, 41,415 single cells were carried forward for analysis. Unsupervised clustering analysis and lineage identification revealed two divergent cellular patterns in DBA compared with age-matched control BM that segregated with genotype: a selective loss of erythromegakaryocyte (E/MK) progenitors in RPS-DBA, but relative preservation of the erythroid developmental trajectory in RPL-DBA, at the expense of megakaryopoiesis (Fig 1a). Gene Set Enrichment Analysis (GSEA) of differentially expressed genes between control and DBA HSPC clusters revealed p53-mediated apoptosis, TNFa-, IFNa- and IFNg-mediated inflammatory pathways in DBA EP. Although these pathways were enriched across all HSPC populations irrespective of genotype, they were detected at an earlier stage of the stem cell hierarchy, and more potently, in RPS- versus RPL-EP. Expression of transcriptional targets of the master E/MK transcription factor, GATA1, was significantly upregulated in RPL- versus RPS-DBA EP (Fig 1b), supporting the maintained erythroid program in RPL-DBA HSPC. However, expression of genes denoting erythroid differentiation, including adult haemoglobin (Hb) genes, was significantly elevated in RPL-DBA, suggesting aberrant accelerated differentiation to EB. These findings were confirmed by immunophenotypic examination of patient BM and bulk RNAseq of RPL-EB. Additionally, single-cell clonogenic assays of RPL-DBA EP showed severe qualitative defects. Thus, although erythroid commitment occurs in RPL-DBA, it is coupled with accelerated maturation beyond EP to functionally impaired mature EB, enriched in inflammatory and p53 pathways. Finally, we analysed the clinical characteristics of the 161 patients comprising the U.K DBA registry. In line with the milder erythroid specification defect, patients with RPL-DBA (n=44) presented with anaemia later (P=0.004), and with a higher average Hb concentration (P=0.04), than those with RPS-DBA (n=63). Furthermore, we identified higher corticosteroid responses in RPL-DBA, assessed at 6 months post initiation (P=0.006), consistent with our findings in RPL-DBA of preservation of the cellular EP populations that are targeted by corticosteroids. Impact: In conclusion, a preserved but distinct erythroid developmental trajectory, characterised by accelerated differentiation, underpins a milder haematological phenotype in RPL-DBA. Furthermore, we reveal the first single-cell transcriptomic dataset from haematopoietic cells in a ribosomopathy, uncovering novel cell intrinsic and extrinsic pathogenetic insights into failing erythropoiesis in DBA. Integration of these data with clinical genomics and phenomics provides a paradigm by which single cell approaches can be used to decipher genotype-phenotype relationships in Mendelian genetic disorders. Disclosures Mead: Novartis: Consultancy, Honoraria, Other: travel, accommodations, expenses, Research Funding, Speakers Bureau; Celgene/BMS: Consultancy, Honoraria, Other: travel, accommodations, expenses, Research Funding; Abbvie: Consultancy; CTI: Consultancy; Gilead: Consultancy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".