Single cell analysis reveals the roles and regulatory mechanisms of type-I interferons in Parkinson's disease.
The main results reproduced, with only marginal, non-material deviations.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- Nothing in this column.
- 🟡Could not use the authors’ exact input data
- 🟡Reported values were only indirectly comparable
- 🟡A deviation arose in the data or preprocessing
- 🔴A deviation was attributed to the published material
- 🟡Reported values were not (fully) derivable from the shared data
- 🟡The deviation was non-trivial in magnitude
- 🟡The central claim did not (fully) hold under reproduction
- 🟡Overall, the reproduction showed a material discrepancy
A 0–100 reproducibility-quality score from the per-question grades, shown as a z-score: standard deviations above (+) or below (−) the mean of comparable assessments.
▸Reproduction agent’s raw note
Described well enough ONLY for the bulk validation pipeline. The paper's central single-cell analysis (GSE157783: Seurat CCA + SCENIC + AUCell IFN-I scoring + monocle) ships NO code (repo = bulk-seq R script + AlphaFold notebook) -> that part is a docs_insufficient drop and was not attempted. We faithfully reran the one shipped pipeline (2.Scripts_bulk_seq.R) on GSE49036 (8 control / 20 Braak PD, GPL570) with limma 3.50.3 (== paper), Hallmark v7.5.1 (== paper), GSVA 1.42 (paper 1.18). Results: NFATc2 and RUNX2 reproduce as UP in PD/Braak5/6 (matches Fig 7E, directional, modest/borderline-significant). IRF5 does NOT reproduce the paper's 'contrary' (down) trend - we see a weak non-significant UP (mismatch, but effect negligible). GSVA reproduces 14 significant Hallmark pathways dominated by immune/inflammatory sets consistent with the neuroinflammation/IFN thesis; the two interferon hallmark sets are positively enriched in PD but narrowly miss the p<0.05 cutoff (IFN-gamma p=0.051) - plausibly due to GSVA 1.18 vs 1.42 and control-vs-(all-Braak) grouping vs a possible Braak5/6-only contrast. PCA reproduces outlier detection (GSM1192710 clearly extreme). NOT attempted: single-cell GSE157783 (no code), GSE7621/GSE26927 bulk (other platforms, repo wires only GSE49036), AlphaFold2.ipynb (stochastic, no gradeable claim), wet-lab. Shipped script is not runnable verbatim (undefined vars GSE49036_sm/GSE49036_ann; var-name typos fixed). All grades PROVISIONAL - human audit required.
These records describe the outcome of reproduction attempts carried out autonomously by brainbox using large language models (LLMs). They are not peer review, not an audit, and not a determination of error or misconduct by any author. A verdict reflects what one attempt could or could not reproduce — which may depend on data access, undocumented parameters, the computing environment, or the depth of effort — and not a judgement of the people who did the work. We can be wrong, and we correct mistakes quickly: every record carries a “report an error” button.
Assessment versions
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v1 current initial assessment Score 55assessed: 2026-06-15 ⛓ b1f6bf5ab486
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Updated or fixed a deposit, or is there an erratum? Ask us to re-run the metrics. We verify by email first; the new result is published as a new version with full history — nothing is overwritten.
Provenance — full disclosure
When this reproduction was carried out, which methodology version was used, and by whom — so the record can be audited and checked independently.
- Reproduced
- 2026-06-15
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-15no human curator yet
- Last updated
- 2026-08-05
Provisional, curator- or AI-assessed, and independently checkable. A reproduction outcome states what one attempt could reproduce — not a judgement of the authors.
Deep full-text extraction
Model: opusThe study tests how type I interferon (IFN-I) activity is distributed across midbrain cell types in Parkinson's disease and which transcription factors regulate aberrant IFN-I responses and microglial pro-inflammatory activation, hypothesizing that NFATc2 drives the type I interferon response and neuroinflammation in PD.
- ★ Microglia, endothelial cells, and pericytes exhibit the highest type I interferon (IFN-I) activity among PD midbrain cell types, with microglia showing markedly higher activity in PD. finding
- ★ Microglia in the PD midbrain adopt a pro-inflammatory activation state along their differentiation trajectory. finding
- ★ NFATc2 is a key transcription factor that is significantly up-regulated and drives ISG expression and microglial activation in PD. mechanism
- ★ Suppression of NFATc2 in MPP+-induced BV2 cells reduces IFN-β, impedes STAT1 phosphorylation, and attenuates NF-κB pathway activation. mechanism
- ★ Downregulation of NFATc2 in microglia mitigates detrimental effects on SH-SY5Y neuronal cells co-cultured in conditioned medium. finding
- An IFN-I-stimulated gene set (ISGs) intersecting cell-subcluster DEGs with the Interferome database, scored per cell with AUCell, can quantify single-cell IFN-I activity. method
- Geneformer in silico perturbation combined with SCENIC regulatory network analysis identifies regulators of the microglial IFN-I phenotype transition. method
- TLR1, TLR5, TLR7, and TLR8 are increased in PD and mainly localized to microglia. finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| single-cell RNA sequencing (scRNA-seq) reanalysis | human midbrain, 5 PD patients and 6 healthy controls (GSE157783) | none (disease vs control) | cell type composition, gene expression, IFN-I activity (AUCell), pseudotime trajectory, SCENIC regulon activity | — |
| in silico gene perturbation | PD microglia (high vs low IFN-I score) | computational gene deletion | genes driving high-to-low IFN-I score transition | Geneformer |
| bulk microarray/transcriptomic GSVA analysis | human substantia nigra PD datasets (GEO) | none (PD vs control) | DEGs (limma) and pathway enrichment, validation of key TF expression | — |
| immunofluorescence staining | MPTP-induced PD mouse model (male C57BL mice) midbrain | MPTP 30 mg/kg ip daily x5 days | Iba1 (microglia) and tyrosine hydroxylase expression | Leica confocal laser scanning microscope |
| Western blotting | BV2 microglia, SH-SY5Y cells, mouse midbrain tissue | MPP+ treatment and si-NFATc2 knockdown | NFATc2, STAT1, p-STAT1, IRF9, BAX, BCL-2, p65, p-p65, IκBα, p-IκBα, GAPDH | — |
| ELISA | BV2 cell culture supernatants | MPP+ ± si-NFATc2 | IL-1β, IL-6, TNF-α, IFN-α, IFN-β concentrations | Solaibao and Jianglai ELISA kits |
| conditioned-medium co-culture apoptosis assay | SH-SY5Y cells co-cultured with BV2 conditioned medium | CM from CON, MPP+, si-NC+MPP+, si-NFATc2+MPP+ groups | SH-SY5Y apoptosis level | — |
| BV2 microglial cell model with siRNA knockdown | BV2 microglial cells | MPP+ 0.5 mM 24 h ± si-NFATc2 | NFATc2 expression, downstream IFN/inflammation signaling | — |
- ▲ In PD microglia, 1352 of 2639 cells showed high IFN-I activity versus 407 of 1165 in controls p = 2.111e-20
- ▲ Endothelial cells in PD showed higher high-IFN-I fraction (649/717) versus control (943/1008) p = 0.0252
- – Pericytes showed no significant difference in high-IFN-I activity (180/572 PD vs 209/651 control) p = 0.8597
- – Microglia and astrocytes increased while oligodendrocytes and dopaminergic neurons decreased in PD midbrain; miloR confirmed higher relative microglial abundance in PD
- ▲ Pro-inflammatory microglial state (state 2/cell fate1) expressed cluster-2 genes (GPNMB, HSPA5, IL1RAP) enriched for myeloid leukocyte activation and neuron death
- ▼ NFATc2 suppression reduced IFN-β, decreased STAT1 phosphorylation, and attenuated NF-κB activation in MPP+-induced BV2 cells
- ▲ TLR1, TLR5, TLR7, and TLR8 increased in PD, mainly in microglia
- – 3883 of 39,024 cells exceeded the IFN-I AUC threshold of 0.273, mainly microglia, endothelial cells, and pericytes
- pvalue 2.111e-20 (high IFN-I microglia PD (1352/2639) vs control (407/1165))
- pvalue 0.0252 (high IFN-I endothelial cells PD (649/717) vs control (943/1008))
- pvalue 0.8597 (high IFN-I pericytes PD (180/572) vs control (209/651))
- count 39,024 single nuclei (21,124 control, 17,900 PD) (cells retained after QC across 11 samples)
- count 469 ISGs (IFN-I-stimulated gene set from Interferome database)
- other AUC threshold 0.273; 3883 cells exceeded (IFN-I activity scoring cutoff)
- count 10 cell subsets / 32 clusters (cell types identified from PD midbrain scRNA-seq)
- other MPP+ 0.5 mM for 24 h; MPTP 30 mg/kg ip daily x5 days (PD model perturbation doses)
Statistical methods review
Model: opusA neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.
This is primarily a single-cell RNA-seq computational study (GSE157783; 5 PD patients, 6 controls) using Seurat for QC/integration/clustering, AUCell for IFN-I activity scoring, miloR for differential abundance, Monocle for pseudotime, pySCENIC for regulatory network inference, Geneformer for in silico perturbation, and limma/GSVA for bulk transcriptomic validation, complemented by wet-lab MPTP mouse and MPP+/BV2 cell experiments. For the experimental validation, data are reported as mean ± SD; two-group comparisons used Student's t-test and multi-group comparisons used one- or two-way ANOVA followed by Benjamini–Hochberg correction. Categorical comparisons of high-IFN-I cell proportions between groups were reported with exact p-values (e.g., p = 2.111e-20).
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Student's t-test (two-group comparisons) | Comparisons between two groups in experimental validation (e.g., ELISA cytokines/IFN, western blot quantification) | minimum of three independent biological replicates | not stated |
| One-way and two-way ANOVA followed by Benjamini–Hochberg correction | Comparisons among multiple groups (e.g., CON/MPP+/si-NC/si-NFATc2 BV2 groups) | minimum of three independent biological replicates | not stated |
| FindAllMarkers differential expression (Wilcoxon-type marker test, adjusted p reported) | Cluster marker identification (|log2FC| ≥ 0.25, expression ratio ≥ 0.25, adjusted p < 0.05) | — | na |
| limma differential expression | DEGs in bulk substantia nigra transcriptomic datasets (|log2FC| > 0.25, p < 0.05) | — | na |
| GSVA pathway enrichment (p < 0.05, FDR < 0.25) | Pathway enrichment between PD and control groups in bulk data | — | na |
| Comparison of high-IFN-I-scoring cell proportions between groups (exact p-values reported; test not named) | Fig 3D microglia (p=2.111e-20), endothelial (p=0.0252), pericytes (p=0.8597) | per-cell counts within each subset (e.g., 2639 PD vs 1165 control microglia) | not stated |
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Experimental data were summarized as mean ± standard deviation (SD).↳ Could also: Reporting could additionally include a 95% confidence interval or showing individual data points alongside the mean. — For the small replicate numbers used (~three biological replicates), plotting individual points and a CI also conveys the spread and the precision of the estimate, which many journals encourage for transparency.
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Two-group comparisons used Student's t-test with normality/variance assumptions not explicitly stated.↳ Could also: A Welch's t-test (unequal variances) or a nonparametric Mann–Whitney U test could also be applied, optionally with a stated normality check. — With small n, Welch's correction relaxes the equal-variance assumption and a rank-based test avoids reliance on normality, so either can be a robust complement depending on the data distribution.
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Differences in the proportion of high-IFN-I-scoring cells between PD and control were assessed with per-cell p-values.↳ Could also: A test that accounts for the nested structure of cells within a limited number of donors (e.g., a mixed-effects model or aggregating to per-sample proportions) could also be used. — Treating donors as the replication unit also addresses pseudoreplication from many cells per individual, which can give a more conservative estimate of between-group differences in scRNA-seq.
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Multi-group experimental comparisons used ANOVA followed by Benjamini–Hochberg correction.↳ Could also: A post-hoc test such as Tukey's HSD or Dunnett's (against the control) could also follow the ANOVA. — Tukey/Dunnett are designed specifically for pairwise mean comparisons after ANOVA and control family-wise error for that family, which is a common alternative to an FDR-based correction in small designed experiments.
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Differential abundance and DEG significance relied on default thresholds (e.g., |log2FC| cutoffs and adjusted p < 0.05).↳ Could also: Reporting effect sizes (fold changes with confidence intervals) alongside p-values could also be provided. — Effect-size reporting complements significance testing by conveying the magnitude and uncertainty of differences, which aids interpretation and cross-study comparison.
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Bulk validation used limma for DEGs and GSVA for pathway scoring with p < 0.05 thresholds.↳ Could also: limma's empirical-Bayes moderated statistics with adjusted (FDR) p-values, and pathway methods such as GSEA or camera, could also be reported. — Applying multiplicity adjustment to the DEG list and using competitive/self-contained gene-set tests can add complementary control of false positives across the many genes and pathways examined.
Result convergence & founder nodes
Findings this paper shares with others that ran a comparable experiment. A node’s strength is how many independent papers report it (replication breadth) — not how often it is cited, so a heavily-replicated but under-cited founder still stands out.
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Type I interferon signaling activity is elevated in endothelial cells in PD versus control human midbrainscRNA-seq human midbrain endothelial cell up 2024×1papers★ This paper is the founder (earliest)
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GPNMB is upregulated in the pro-inflammatory PD microglial state enriched for myeloid leukocyte activation and neuron death gene setsscRNA-seq human midbrain microglia up 2024×1papers★ This paper is the founder (earliest)
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TLR7 (alongside TLR1, TLR5, and TLR8) is upregulated in PD human midbrain predominantly in microgliascRNA-seq human midbrain microglia up 2024×1papers★ This paper is the founder (earliest)
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Type I interferon signaling activity is elevated in microglia from PD patients compared to healthy controls in human midbrainscRNA-seq human midbrain microglia up 2024×1papers★ This paper is the founder (earliest)
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Type I interferon signaling activity does not differ significantly in pericytes between PD and control human midbrainscRNA-seq human midbrain pericyte none 2024×1papers★ This paper is the founder (earliest)
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Microglia are more abundant in PD human midbrain while dopaminergic neurons and oligodendrocytes are depletedscRNA-seq human midbrain up 2024×1papers★ This paper is the founder (earliest)
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Nfatc2 knockdown in MPP+-treated BV2 microglia reduces IFN-β secretion, STAT1 phosphorylation, and NF-κB activationwestern-blot bv2 down 2024×1papers★ This paper is the founder (earliest)
Citation network
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Data lineage
The datasets this paper uses (text-mined from the full text via Europe PMC), and which other assessed papers stand on the same data. A shared dataset is a factual link — not a judgement.
Downstream reach in the literature
26 downstream papers · 1 datasetsHow widely the datasets deposited by this paper are reused across the whole literature (Europe PMC), beyond our assessed set. This is a factual dependency map — reusing a public dataset is normal, good science. It is not a judgement on the downstream papers; the only verdict here is this paper's own, with its cited rationale.
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- Single-Cell Transcriptomics Uncovers Cellular Hetero... 2022 · 17 cites
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
scope.md — pmid-38566100
Paper: Quan et al. 2024, Cell Commun Signal. "Single cell analysis reveals the roles and regulatory mechanisms of type-I interferons in Parkinson's disease." PMID 38566100 / PMC10985960 / DOI 10.1186/s12964-024-01590-1.
Repo: github.com/qneurolab/IFN-I-in-PD @ 758e176a97272fcd41f580dcb5523a758aaaaa50 (default branch main, pushed 2026-01-17, 44 KB, no license). Repo contains EXACTLY TWO files:
2.Scripts_bulk_seq.R(4226 B) — bulk microarray pipeline (GEOquery+limma+GSVA).AlphaFold2.ipynb(34922 B) — ColabFold protein-structure notebook.
In scope (pipeline-derived, reproducible)
The shipped 2.Scripts_bulk_seq.R implements a bulk microarray validation pipeline.
As written it loads GSE49036 (substantia nigra, Affy U133 Plus 2.0). Pipeline steps:
load series matrix -> filter samples (title ~ "Control|BR") -> group control vs disease
-> normalizeBetweenArrays -> probe->gene-symbol collapse (max-median, hgu133plus2.db)
-> PCA (one outlier removed per paper) -> GSVA(ssGSEA, kcdf=Poisson, Hallmark h.all.v7.5.1)
-> limma between groups -> gene boxplots for NFATc2/RUNX2/IRF5.
Reproduce these CLEARLY-SPECIFIED outputs and compare to Fig. 7 claims:
- C1 NFATc2 up in PD (Braak 5/6) vs control, GSE49036 [Fig 7E]
- C2 RUNX2 up in PD (Braak 5/6) vs control, GSE49036 [Fig 7E]
- C3 IRF5 contrary trend, GSE49036 [Fig 7E]
- C4 GSVA Hallmark pathways significant (p<0.05 & FDR<0.25) incl. IFN [Fig 7B]
- C5 PCA identifies an outlier sample to remove
Out of scope (no shipped code / not pipeline-comparable)
- ENTIRE single-cell analysis (GSE157783; Seurat CCA, SCENIC, AUCell, monocle, cell-type annotation, IFN-I scoring) — paper's MAIN result, but NO code in repo (only "2.Scripts_bulk_seq.R" exists; the implied "1.Scripts_single_cell" is absent). -> docs_insufficient for the SC portion.
- AlphaFold2.ipynb structure prediction — stochastic, GPU, no numeric claim to grade.
- Wet-lab (MPTP mouse, BV2/MPP+, IFN-β, STAT1, western blot) — out of scope.
- GSE7621 & GSE26927 gene-direction claims: same pipeline, different platforms; the repo only wires GSE49036. Attempted as a bonus if cheap; primary = GSE49036.
Notes / discrepancies in shipped code (flag, not fabrication)
- Script references undefined vars:
GSE49036_sm@annotation,GSE49036_ann(annotation table is built asann_49036) -> script is NOT runnable verbatim; variable-name typos fixed in our faithful re-implementation, logic unchanged. - Data-availability text typo "GSE99036" (should be GSE49036).
- GSVA called with kcdf="Poisson" on continuous microarray data (methods oddity).
- Paper text: NFATc2/RUNX2 elevated specifically at "Braak stages 5/6"; the shipped load fn groups ALL Braak (BR*) as "disease". We report both groupings.
Assessments & scoring basis
Each contributor’s verdict, the per-question basis, and the auditable, itemised worksheet behind it.
An automated assessment. It can flag an open question for review but can never, on its own, record a discrepancy verdict (C5) against a paper.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
We faithfully reran the only shipped pipeline (bulk 2.Scripts_bulk_seq.R on GSE49036): NFATc2/RUNX2 reproduce as up in PD/Braak5/6 (Fig 7E direction ✓) and the GSVA gives 14 significant immune/inflammatory Hallmark sets supporting the neuroinflammation thesis, but the two type-I IFN sets — the paper's actual point — narrowly miss significance (IFN-γ p=0.051, IFN-α p=0.073) and IRF5 flips sign (paper down, we see weak up). The decisive issue is on the authors' side: the paper's MAIN single-cell GSE157783 analysis (Seurat/SCENIC/AUCell/monocle) ships no code, so the central IFN-I claims cannot be audited from the deposited artifacts. Deviations in the testable bulk part are moderate and plausibly explained by GSVA version (1.18 vs 1.42) and self-chosen grouping; the core conclusion is therefore only limitedly confirmed and the headline result is unverifiable — solid-but-yellow, short of demonstrated fabrication.
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Reproduction footprint
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