Immunophenotyping of peripheral blood mononuclear cells in tuberous sclerosis complex
Bibliographic record
Abstract
Abstract Tuberous sclerosis complex (TSC) is a multisystem disorder caused by loss-of-function mutations in TSC1/2 proteins. This results in constitutive mTOR activation and predisposes to the development of benign tumours, with renal angiomyolipomas (AMLs) and tuber-related drug-resistant epilepsy (DRE) being major causes of morbidity and mortality in adults. Despite the central role of mTOR in leukocyte biology and the beneficial impact of mTOR inhibitors in TSC, the role of the immune system and inflammation in the development of tumours and DRE in people with TSC remains unknown. Using peripheral blood mononuclear cells (PBMCs) and serum from people with TSC, healthy controls (HC) and non-TSC DRE, we employed flow cytometry and multiplex assays to interrogate the immune profile associated with chronic loss of mTOR inhibition. We found that higher levels of the astroglial activation marker GFAP are elevated in TSC and show high intergenotype variability. We also observed differences in circulating immune cell populations, cytokines, chemokines and growth factors related to TSC. We found a higher proportion of B cells in parallel with increased total IgG but a reduction in IL-2 and IL-7 and a lower frequency of T cells. TSC with vs without AML showed differences in CD4:CD8 T cells ratio, monocytes and dendritic cells frequencies. Finally, loss of TSC1/2 affected T cell polarization, leading to an increased proportion of Tc17 CD8+ T cells, especially in subjects with DRE. Overall, our findings indicate TSC is associated with increased blood biomarkers for inflammation, glial activation, and distribution and profile of circulating PBMCs compared to controls.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".