Autoantibodies to Thrombopoietin and the Thrombopoietin Receptor in Patients with Immune Thrombocytopenia
Bibliographic record
Abstract
Abstract Background: Primary immune thrombocytopenia (ITP) is an autoimmune bleeding disorder caused by autoantibodies against platelet glycoproteins (GP). These autoantibodies are detected in only 40-60% of ITP patients even when sensitive techniques are used. Our understanding of the mechanisms of ITP is limited by the variability in clinical presentation, varied differences in treatment responses and the lack of reliable biomarkers. Several studies have exploited the possibilities of other immune-mediated mechanisms to account for low platelet counts in the absence of detectable antibodies. Thus, we hypothesized that other autoantibodies that target antigens involved in the platelet lifecycle can be important in ITP, such as thrombopoietin (TPO) and the thrombopoietin receptor (cMpl). The objective of this study was to evaluate the frequency and clinical significance of autoantibodies against TPO and cMpl in patients with ITP compared to patients with other thrombocytopenic disorders and healthy controls. Methods: We tested well-defined adult ITP patients with a platelet count less than 100 x109/L and ITP patients in remission (platelets > 100,000) all of whom had not received any immune-modulating treatments in the previous 3 months. We also tested patients with other immune-mediated platelet disorders, non-immune thrombocytopenia and healthy controls. Patients with immune-mediated platelet disorders had anti-phospholipid syndrome (APS); heparin induced thrombocytopenia (HIT); or thrombotic thrombocytopenic purpura (TTP). Patients with non-immune thrombocytopenia had hypersplenism with documented splenic enlargement; familial thrombocytopenia; or myelodysplastic syndrome. Samples were tested for circulating antibodies against TPO or cMpl using newly developed enzyme immunoassays (EIAs) and for antibodies against platelet glycoproteins (GPIIb/IIIa and GPIb/IX) using the antigen capture assay. Results: Among patients with active ITP, 36/42 (86%) had antibodies to TPO or c-Mpl: 4/42 (10%) had anti-TPO autoantibodies only and 5/42 (12%) had anti-cMpl autoantibodies only and 15/42 (36%) had both. Among patients with ITP in remission, 8/15 (53%) had autoantibodies to TPO or cMpl. Autoantibodies were not detected in healthy controls; however, all patients with non-immune thrombocytopenia had circulating autoantibodies to TPO or c-Mpl (10/10, 100%): 1/10 (10%) had anti-TPO autoantibodies only and 1/10 (10%) had anti-cMpl autoantibodies only and 8/10 (80%) had both. We also found antibodies against TPO and cMpl in patients with other immune-mediated platelet disorders. Among HIT patients (n=26), 73% had antibodies to TPO and 50% had antibodies to cMpl; among TTP patients (n=16), 31% had antibodies to TPO and 13% had antibodies to cMpl; and among APS patients (n=17), 29% had antibodies to TPO and 47% had antibodies to cMpl. Platelet bound antibodies to GPIIb/IIIa, GPIb/IX or both were detected in 18/42 (43%) active ITP samples; 6/15 (40%) remission ITP samples; and 2/10 (20%) patients with thrombocytopenia from non-immune causes. ITP patients with anti-TPO or anti-cMpl antibodies required fewer ITP therapies before remission was achieved compared with patients who had anti-GP autoantibodies. Conclusions: Testing the entire panel of autoantibodies that included anti-TPO, anti-cMpl and anti-GP, we were able to identify all patients with active ITP; however, we could not distinguish between patients with ITP and other thrombocytopenic syndromes. Disclosures Arnold: Novartis: Consultancy, Research Funding; Bristol Myers Squibb: Consultancy; UCB: Consultancy; Amgen: Consultancy, Research Funding.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".