Frequencies of Circulating Immune Cells in Patients with Parkinson’s Disease: Correlation with MDS-UPDRS Scores
Bibliographic record
Abstract
BACKGROUND: Parkinson's Disease (PD) is associated with dysregulated/chronic inflammation. The immune system has multiple roles including beneficial effects such as clearing alpha synuclein aggregates. However, peripheral immune cells entering the brain may also contribute to inflammation and neurodegeneration. To identify which cells might have a negative impact and could be potential therapeutic targets, we compared immune signatures of patients and healthy controls. METHODS: Multicolor flow cytometry was used to determine the frequencies of major immune cell subsets in peripheral blood mononuclear cells (PBMCs) of PD patients and controls. Because of the major impact of Cytomegalovirus (CMV) infection on the distribution of immune cell subsets, particularly cluster of differentiation (CD)8+ T-cells, all participants were tested for CMV seropositivity. RESULTS: Although the cohort of 35 PD patients exhibited the well-established T-cell differentiation signature driven by CMV infection, there were no differences in the frequencies of differentiated or pro-inflammatory T-cells, B-cells or natural killer cells (NK-cells) attributable to the disease. However, percentages of myeloid-derived suppressor cells (MDSCs) were higher in PD patients than controls. Moreover, percentages of CD14+CD16+ (intermediate) monocytes expressing the C-C chemokine receptor type 5 (CCR5) correlated with disease severity assessed by the Movement Disorder Society's revised version of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score and disease duration. CONCLUSIONS: A comprehensive evaluation of the major subsets of circulating immune cells in PD patients revealed differences in myeloid cells between PD and healthy controls and some correlation of monocyte abundance with disease severity.
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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 | 0.001 |
| 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) | 0.000 | 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".