Mitochondrial transfer between neurons and gliaΒΆ
Analysis ID: SDA-2026-04-01-gap-20260401231108
Date: 2026-04-02
Domain: neurodegeneration
Hypotheses Generated: 7
Knowledge Graph Edges: 0
Key HypothesesΒΆ
- Astrocytic Connexin-43 Upregulation Enhances Neuroprotective Mitochondrial Donation (score: 0.630)
- Miro1-Mediated Mitochondrial Trafficking Enhancement Therapy (score: 0.570)
- PINK1/Parkin-Independent Mitophagy Bypass for Enhanced Donor Mitochondria (score: 0.550)
- Gap Junction Hemichannel Modulation for Controlled Mitochondrial Exchange (score: 0.470)
- Optogenetic Control of Mitochondrial Transfer Networks (score: 0.450)
- Microglia-Derived Extracellular Vesicle Engineering for Targeted Mitochondrial Delivery (score: 0.430)
- Synthetic Biology Approach: Designer Mitochondrial Export Systems (score: 0.400)
This notebook presents a computational analysis including differential gene expression, pathway enrichment, and multi-dimensional hypothesis scoring. Data is simulated based on known biology from the Allen Brain Cell Atlas (SEA-AD) and published literature.
1. Setup and Data GenerationΒΆ
Generated expression data for 20 genes x 5 cell types Samples per condition: 50 Primary cell type: Astrocytes
2. Differential Expression HeatmapΒΆ
Log2 fold change of gene expression between disease and control samples across cell types. Significance: * p<0.05, ** p<0.01, *** p<0.001 (Mann-Whitney U test).
Significant changes (p < 0.05): 13 / 100
3. Volcano Plot: Astrocytes ExpressionΒΆ
Differential expression in astrocytes β the primary cell type of interest for this analysis. Red = upregulated in disease, blue = downregulated. Dashed line = p=0.05 threshold.
Significantly upregulated: 3 Significantly downregulated: 0
4. Statistical AnalysisΒΆ
Comprehensive statistical testing including non-parametric Mann-Whitney U tests, effect sizes (Cohen's d), and one-way ANOVA for cell-type variation.
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STATISTICAL ANALYSIS SUMMARY
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Significant results (p < 0.05): 13 gene-cell type pairs
Gene Cell_Type Log2FC P_value Cohens_d Effect
MIRO1 Astrocytes 1.134048 2.213283e-10 1.360469 Large
PRKN Microglia 1.077872 1.165920e-08 1.258707 Large
MIRO2 Astrocytes 1.097823 6.615677e-08 1.177637 Large
PINK1 Microglia 0.994192 1.523936e-07 1.132786 Large
CD38 Astrocytes 1.110219 1.038120e-06 1.162193 Large
NDUFS1 Exc Neurons -0.664570 5.823820e-06 -0.879632 Large
OPA1 Oligodendrocytes -0.576820 3.374007e-05 -0.918854 Large
SIRT3 Exc Neurons -0.556174 2.110339e-04 -0.812028 Large
PPARGC1A Exc Neurons -0.588275 2.289302e-04 -0.730995 Medium
TFAM Exc Neurons -0.520531 2.690772e-04 -0.699383 Medium
MFN2 Oligodendrocytes -0.583182 2.915412e-04 -0.651340 Medium
ATP5A1 Exc Neurons -0.522119 4.557378e-04 -0.771362 Medium
MFN2 Inh Neurons 0.247168 4.904669e-02 0.344468 Small
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ONE-WAY ANOVA: Expression Variation Across Cell Types (Disease)
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MIRO1 F= 24.35 p=5.60e-17 ***
MIRO2 F= 22.74 p=5.41e-16 ***
TNT1 F= 0.56 p=6.90e-01 ns
CD38 F= 13.04 p=1.21e-09 ***
PINK1 F= 14.49 p=1.24e-10 ***
PRKN F= 6.83 p=3.18e-05 ***
MFN2 F= 5.09 p=5.84e-04 ***
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MULTIPLE TESTING CORRECTION (Bonferroni)
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Tests performed: 13
Significant before correction: 13
Significant after Bonferroni: 12
5. Pathway Enrichment AnalysisΒΆ
Hypergeometric test for enrichment of analysis target genes in curated biological pathways (Reactome/KEGG-style). Identifies which molecular processes are overrepresented.
Pathway Enrichment Results:
Pathway Overlap Overlap_Genes Fold_Enrichment P_value Significant
Tunneling Nanotube Formation 4 MIRO2, MIRO1, CD38, TNT1 1904.8 7.875472e-14 True
Mitophagy (PINK1/Parkin) 2 PINK1, PRKN 952.4 1.574029e-06 True
Mitochondrial Dynamics 1 MFN2 476.2 2.098425e-03 True
Oxidative Phosphorylation 0 - 0.0 1.000000e+00 False
Mitochondrial Biogenesis 0 - 0.0 1.000000e+00 False
Calcium-Mito Crosstalk 0 - 0.0 1.000000e+00 False
ROS Defense 0 - 0.0 1.000000e+00 False
Extracellular Vesicle Transport 0 - 0.0 1.000000e+00 False
6. Hypothesis Multi-Dimensional ScoringΒΆ
Top hypotheses scored across 6 key dimensions: mechanistic plausibility, evidence strength, novelty, feasibility, therapeutic impact, and druggability.
7. Knowledge Graph EdgesΒΆ
Causal relationships extracted from the multi-agent debate:
| Source | Relation | Target | Confidence |
|---|---|---|---|
| (none) | - | - | - |
Total edges: 0
MethodologyΒΆ
This analysis was generated by SciDEX's multi-agent scientific debate system:
- Theorist generates novel hypotheses based on known biology
- Skeptic challenges assumptions and identifies weaknesses
- Domain Expert assesses druggability, feasibility, and clinical relevance
- Synthesizer ranks hypotheses and extracts knowledge graph edges
Gene expression data is simulated based on published SEA-AD atlas findings (Allen Institute for Brain Science).
Generated: 2026-04-02 22:03 UTC Platform: SciDEX Source: GitHub