Platelet GPIba Is Important for Thrombopoietin Production and Thrombopoietin-Induced Platelet Generation
Bibliographic record
Abstract
Abstract Background: Platelets are generated from megakaryocytes in the bone marrow and play a key role in hemostasis. GPIba is the major subunit in the GPIb-IX complex expressed on platelets and megakaryocytes (MKs). Deficiency of GPIba results in Bernard Soulier Syndrome (BSS), a severe bleeding phenotype characterized by thrombocytopenia and abnormal platelet morphology. The generation of megakaryocytes and platelets is regulated by the hematopoietic growth factor, thrombopoietin (TPO). In patients with thrombocytopenia, the TPO receptor agonists and recombinant TPO (rTPO) have been used to stimulate thrombopoiesis. TPO production primarily occurs in liver parenchymal cells with minor amounts synthesized in other tissues. The major clearance mechanism of TPO from circulation is via interaction between TPO and its receptor, c-Mpl, following which the c-Mpl-TPO complex undergoes internalization and degradation. However, whether it is the production or clearance of TPO the main regulator of circulating TPO levels has been debated but remains unclear. The prevailing theory was that hepatic TPO is generated constitutively, and the levels of circulating TPO are fine-tuned by its uptake and metabolism in platelets and megakaryocytes. Recently, this concept was modified by studies in Ashwell-Morell receptor (AMR) deficient mice, which highlighted the important role played by platelets in the regulation of hepatic TPO mRNA expression. As the most glycosylated platelet surface protein, GPIba contributes to chilled platelets clearance viahepatocytes, as well as antibody-mediated thrombocytopenia. However, the relationship between GPIba and plasma TPO has not been explored Methods and Results: We observed a significant decrease (approx. 3 fold) of TPO levels in both plasma and sera of GPIba-/- mice compared to wild type (WT) controls. Given the enlarged size of GPIba-/- platelets compared to WT, we investigated whether the low circulating TPO levels could be due to increased TPO clearance. Interestingly, we found similar levels of intracellular TPO in WT and GPIba-/- platelets, and the capacity to adsorb TPO in vitro was not enhanced. Further, we observed GPIba-/- platelets, surprisingly, have less c-Mpl expression compared to WT. Therefore, the decreased circulating TPO levels in GPIba-/- mice is unlikely due to enhanced TPO clearance. We next quantified TPO mRNA from hepatic liver cells as they are known as the major source of TPO. Consistent with the low circulatory TPO levels, we found reduced hepatic TPO mRNA in GPIba-/- mice, suggesting a deficiency in hepatic TPO generation. To determine whether exogenous platelet transfusions could influence steady-state hepatic TPO production, we transfused WT or GPIba-/- mice with WT or GPIba-/- platelets. Post-transfusion of WT, but not GPIba-/- platelets elevated TPO levels to around 150% in GPIba-/- mice. Additionally, our preliminary data showed that co-culture of hepatocytes with WT, but not GPIba-/- platelets in vitro increased hepatic TPO mRNA expression, further supporting a role for GPIba in TPO generation. To test whether TPO can equally induced platelet generation in GPIba-/- and WT mice. We injected rTPO into the two groups of mice, and found that in contrast to WT controls, rTPO did not significantly increase the platelet number of GPIba-/- mice in the circulation. Conclusion: Our data demonstrated that GPIba is important for TPO generation in liver and is necessary for TPO-induced platelet generation. These discoveries may have significant implications in TPO therapy in ITP. Disclosures No relevant conflicts of interest to declare.
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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) | 0.003 | 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".