Digital biomarkers and AI-driven early detection of neurodegeneration¶
Analysis ID: SDA-2026-04-01-gap-012
Date: 2026-04-02
Domain: neurodegeneration
Hypotheses Generated: 7
Knowledge Graph Edges: 20
Key Hypotheses¶
- Multi-Modal Stress Response Harmonization (score: 0.605)
- Digital Twin-Guided Metabolic Reprogramming (score: 0.601)
- Circadian-Synchronized Proteostasis Enhancement (score: 0.586)
- Smartphone-Detected Motor Variability Correction (score: 0.574)
- Retinal Vascular Microcirculation Rescue (score: 0.542)
- Vocal Cord Neuroplasticity Stimulation (score: 0.523)
- Ocular Immune Privilege Extension (score: 0.474)
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 Generation¶
Generated expression data for 20 genes x 5 cell types Samples per condition: 50 Primary cell type: Exc_Neurons
2. Differential Expression Heatmap¶
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): 12 / 100
3. Volcano Plot: Exc_Neurons Expression¶
Differential expression in exc_neurons — the primary cell type of interest for this analysis. Red = upregulated in disease, blue = downregulated. Dashed line = p=0.05 threshold.
Significantly upregulated: 0 Significantly downregulated: 5
4. Statistical Analysis¶
Comprehensive statistical testing including non-parametric Mann-Whitney U tests, effect sizes (Cohen's d), and one-way ANOVA for cell-type variation.
====================================================================== STATISTICAL ANALYSIS SUMMARY ======================================================================
Significant results (p < 0.05): 12 gene-cell type pairs Gene Cell_Type Log2FC P_value Cohens_d Effect GFAP Astrocytes 1.112397 3.024757e-10 1.158786 Large S100B Astrocytes 1.202766 3.391081e-09 1.191535 Large YKL40 Astrocytes 1.122073 3.686862e-09 1.263214 Large TREM2 Microglia 0.938236 3.077121e-07 1.073525 Large NEFL Exc Neurons -0.585802 4.055481e-06 -0.742581 Medium NPTX2 Exc Neurons -0.546540 9.454853e-06 -0.718556 Medium VGF Exc Neurons -0.573384 1.340134e-05 -0.775583 Medium SYT1 Exc Neurons -0.579894 1.998422e-04 -0.723576 Medium ENO2 Inh Neurons -0.538817 3.418372e-04 -0.611056 Medium NRGN Exc Neurons -0.485914 4.001627e-04 -0.690989 Medium SNAP25 Exc Neurons -0.553687 4.557378e-04 -0.776096 Medium SNAP25 Inh Neurons -0.584446 4.965991e-03 -0.650239 Medium ====================================================================== ONE-WAY ANOVA: Expression Variation Across Cell Types (Disease) ====================================================================== NEFL F= 6.94 p=2.64e-05 *** NRGN F= 9.74 p=2.49e-07 *** SNAP25 F= 6.85 p=3.06e-05 *** SYT1 F= 4.95 p=7.42e-04 *** VILIP1 F= 0.16 p=9.60e-01 ns FABP3 F= 3.31 p=1.16e-02 * ENO2 F= 4.18 p=2.70e-03 ** ====================================================================== MULTIPLE TESTING CORRECTION (Bonferroni) ====================================================================== Tests performed: 12 Significant before correction: 12 Significant after Bonferroni: 11
5. Pathway Enrichment Analysis¶
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
Biomarker Candidates 3 VILIP1, FABP3, NEFL 1428.6 5.248425e-10 True
Calcium Signaling 2 VILIP1, NRGN 1142.9 1.049528e-06 True
Synaptic Vesicle Cycle 2 SYT1, SNAP25 952.4 1.574029e-06 True
Neurofilament Biology 1 NEFL 476.2 2.098425e-03 True
Amyloid Processing 0 - 0.0 1.000000e+00 False
Tau Pathology 0 - 0.0 1.000000e+00 False
Lipid Metabolism 0 - 0.0 1.000000e+00 False
Neurotrophin Signaling 0 - 0.0 1.000000e+00 False
6. Hypothesis Multi-Dimensional Scoring¶
Top hypotheses scored across 6 key dimensions: mechanistic plausibility, evidence strength, novelty, feasibility, therapeutic impact, and druggability.
7. Knowledge Graph Edges¶
Causal relationships extracted from the multi-agent debate:
| Source | Relation | Target | Confidence |
|---|---|---|---|
| NR3C1 | associated_with | neurodegeneration | 0.612 |
| NR3C1 | interacts_with | CRH | 0.612 |
| NR3C1 | interacts_with | TNFA | 0.612 |
| CRH | associated_with | neurodegeneration | 0.612 |
| CRH | interacts_with | NR3C1 | 0.612 |
| CRH | interacts_with | TNFA | 0.612 |
| TNFA | associated_with | neurodegeneration | 0.612 |
| TNFA | interacts_with | NR3C1 | 0.612 |
| TNFA | interacts_with | CRH | 0.612 |
| PPARGC1A | interacts_with | PRKAA1 | 0.615 |
| PRKAA1 | associated_with | neurodegeneration | 0.615 |
| PRKAA1 | interacts_with | PPARGC1A | 0.615 |
| CLOCK | interacts_with | ULK1 | 0.594 |
| ULK1 | associated_with | neurodegeneration | 0.594 |
| ULK1 | interacts_with | CLOCK | 0.594 |
| DRD2 | associated_with | neurodegeneration | 0.532 |
| DRD2 | interacts_with | SNCA | 0.532 |
| SNCA | associated_with | neurodegeneration | 0.532 |
| SNCA | interacts_with | DRD2 | 0.532 |
| PDGFRB | associated_with | neurodegeneration | 0.506 |
Total edges: 20
Methodology¶
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