Alteration of the platelet transcriptome in chronic kidney disease
Bibliographic record
Abstract
Bleeding and thrombotic disorders are major complications affecting patients with chronic kidney disease (CKD). Exposure of circulating platelets to uraemic toxins and contact with artificial surfaces during dialysis induce platelet abnormalities and alter the platelet proteome. We hypothesised that these changes may be subsequent to changes in the composition and/or regulation of the platelet transcriptome. In this study, we investigated the circulating platelets of 10 CKD patients (i.e. five chronic haemodialysis patients and five stage 4 CKD uraemic patients) and five age- and sex-matched healthy subjects. We observed an alteration of the platelet messenger RNA (mRNA) and microRNA transcriptome in CKD patients. Impaired in uraemic platelets, the levels of some mRNAs and of most microRNAs appeared to be corrected by dialysis, which is consistent with a beneficial effect of dialysis and a mRNA regulatory role of platelet microRNAs. Reduced in platelets of uraemic patients, phosphatidylcholine transfer protein (PCTP) and WD repeat-containing protein 1 (WDR1) were found to be regulated by microRNAs, the latter of which involving hsa-miR-19b, a microRNA increased in platelets of uraemic patients and involved in platelet reactivity. These results suggest that an alteration of microRNA-based mRNA regulatory mechanisms may underlie the platelet response to uremia and entail the development of platelet-related complications in CKD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".