Blood transcriptional profiles distinguish different clinical stages of cutaneous leishmaniasis in humans
Bibliographic record
Abstract
Cutaneous leishmaniasis (CL) is a neglected tropical disease with severe morbidity and socioeconomic sequelae. A better understanding of underlying immune mechanisms that lead to different clinical outcomes of CL could inform the rational design of intervention measures. While transcriptomic analyses of CL lesions were recently reported by us and others, there is a dearth of information on the expression of immune-related genes in the blood of CL patients. Herein, we investigated immune-related gene expression in whole blood samples collected from individuals with different clinical stages of CL along with healthy volunteers in an endemic CL region where Leishmania (L.) tropica is prevalent. Study participants were categorized into asymptomatic (LST+) and healthy uninfected (LST-) groups based on their leishmanin skin test (LST). Whole blood PAXgene samples were collected from volunteers, who had healed CL lesions, and patients with active L. tropica cutaneous lesions. Quality RNA extracted from 57 blood samples were subjected to Dual-color reverse-transcription multiplex ligation-dependent probe amplification (dcRT-MLPA) assay for profiling 144 immune-related genes. Results show significant changes in the expression of genes involved in interferon signaling pathway in the blood of active CL patients, asymptomatics and healed individuals. Nonetheless, distinct profiles for several immune-related genes were identified in the healed, the asymptomatic, and the CL patients compared to the healthy controls. Among others, IFI16 and CCL11 were found as immune transcript signatures for the healed and the asymptomatic individuals, respectively. These results warrant further exploration to pinpoint novel blood biomarkers for different clinical stages of CL.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 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".