Cytokine and Chemokine Levels Correlate with Apoptosis Markers in Platelets of Pediatric Patients with Immune Thrombocytopenia
Bibliographic record
Abstract
Abstract Immune thrombocytopenia (ITP) is defined as an autoimmune disease that leads to platelet clearance by macrophages. It is well known that auto-reactive B cells and CD4+ T-helper (Th) cells, and in particular their cytokines, have been associated with ITP. Cytokines and chemokines are key players in our immune response to recruit different cells, e.g. macrophages and monocytes, to respond to certain inflammatory signals. Specific cytokines (i.e. TNF-a, IFN-g) are known to induce apoptosis in nucleated blood cells. To understand the role of cytokines and chemokines in acute ITP, we studied their plasma levels in 10 pediatric ITP patients at diagnosis with a median platelet count of 3 x 109/L (range < 1 to 22 x 109/L) and compared them with controls: healthy children (n=9; platelet count > 150 x 109/L); and chemotherapy-induced thrombocytopenia patients (cTP; n=9; median platelet count of 12 x 109/L; range: 3-53 x 109/L). ITP patients fulfilled the criteria for acute ITP and presented with mild to moderate bleeding symptoms. The median age at diagnosis was 3.4 yrs (range: 1.6 - 6.5 yrs); blood samples were taken prior to treatment. Luminex technology was used to measure plasma levels of 42 cytokines and chemokines. Markers of platelet apoptosis - activated caspase-3, -8 and -9 - and of platelet activation - CD62P and CD63 expression and PAC-1 binding - were measured by flow cytometry. Distinct plasma cytokine/chemokine patterns were observed in ITP patients compared with controls. Significantly increased levels of the Th1 cell commitment cytokines TNF-α (p < 0.01) and IFN-g (p < 0.05), as well as of the Th2 cytokines IL-6 (p < 0.01), IL-10 (p < 0.01) and IL-13 (p < 0.05), were identified in ITP patients. We have previously shown that there is activation of platelet caspase-3, -8 and -9 at diagnosis in acute paediatric ITP patients compared with controls (Winkler et al, Br J Haematol 2012;156:508). In ITP patients, but not in controls, a negative correlation between eotaxin and caspase- 3 (r2 = 0.72), -8 (r2 = 0.76) and -9 (r2 = 0.53) activity were observed, as well as a negative correlations between GM-CSF and caspase-8 (r2 = 0.52) and -9 (r2 = 0.33). Furthermore, we found a correlation between IL-13 and platelet activation as measured by CD62P (r2 = 0.87) and CD63 (r2 = 0.67) expression in ITP patients but not in controls. In summary, increased plasma levels of the cytokines TNF-α, IFN-g, IL-6, IL-10, and IL-13 were observed in ITP patients at initial presentation, suggesting that these cytokines contribute to the pathogenesis of the disease. Since IL-6 and IFN-g are known to activate macrophages, while higher levels TNF-α, IL-10 and IL-13 in the plasma are signs for activated T cells, our findings are consistent with the current model of ITP, in which activated macrophages induce B and T cells to produce anti-platelet autoantibodies. Our goal is to study the interplay between the immune system and the reduction of platelet count in ITP and to further define apoptosis/activation-related pathways in ITP platelets. Furthermore, we showed a correlation in ITP patients between the chemokine eotaxin and GM-CSF with caspase-3, -8 and -9 activity, and a correlation between IL-13 and platelet activation. Our results imply, that apoptosis and platelet activation at diagnosis in ITP play a role in the development of ITP, but the underlying mechanisms are still unknown and needs to be further evaluated by increasing the patient cohort in our study. 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".