🔬
Analysis Proposal: entities-pnt001 ||| neurofibrillary-tangles
active
analysis proposal
Created: 2026-04-27T08:43:13
By: analysis_proposal_generator
Quality:
50%
✓ SciDEX
ID: analysis_proposal-87376ad7-12e1-4fcb-9bf
Analysis Proposal
Analysis Question
Can we validate the involvement of entities-pnt001 in neurofibrillary-tangles using human postmortem brain transcriptomic and proteomic datasets?
Datasets
Allen Institute for Brain Science Human Brain Atlas (AHBA) – regional transcriptomic data across prefrontal cortex and hippocampusMayo Clinic Brain Bank RNA-seq dataset (MayoRNAseq) – temporal cortex samples from AD and control subjectsReligious Orders and Memory and Aging Project (ROSMAP) – longitudinal clinical and RNA‑seq dataBanner Sun Health Research Institute (Banner) – proteomic profiles of Braak‑staged neurofibrillary tangle pathologyGene Expression Omnibus (GEO) – ArrayExpress dataset for NFT‑enriched vs NFT‑poor brain regions (e.g., GSE124439)
Methods
Step 1: Extract expression values of entities-pnt001 from each dataset and map them to brain region and Braak stage.
Step 2: Perform differential expression analysis (t‑test/Wilcoxon) between NFT‑high (Braak V–VI) and NFT‑low (Braak 0–II) groups.
Step 3: Compute correlation of entities-pnt001 expression with established NFT markers (e.g., AT8 density, total tau, phosphorylated tau).
Step 4: Conduct gene‑set enrichment (GO, KEGG) and overlay protein‑protein interaction networks (STRING, BioGRID) to situate entities-pnt001 among known NFT regulators.
Step 5: Apply Mendelian Randomization (TwoSampleMR) using eQTLs of entities-pnt001 to test a causal effect on NFT burden (quantified by Braak stage or CSF p‑tau levels).
Step 6: Build a multivariate predictive model (elastic‑net regression) linking entities-pnt001 expression, co‑variates (age, sex, APOE genotype) to NFT severity; evaluate via 10‑fold cross‑validation.
Expected Outputs
- Figure 1 – Bar plot of entities-pnt001 expression across NFT severity stages with significance bars
- Figure 2 – Scatter plot with regression line of entities-pnt001 expression vs AT8 density, including Spearman correlation
- Figure 3 – Protein‑protein interaction network diagram highlighting entities-pnt001 and its direct partners, colored by differential expression
- Table 1 – Differential expression summary (log2FC, p‑value, FDR) for entities-pnt001 in each cohort
- Table 2 – Mendelian randomization results (beta, SE, p‑value) for the causal link between entities-pnt001 eQTLs and NFT burden
- Table 3 – Elastic‑net model coefficients and performance metrics (AUC, RMSE) for NFT severity prediction
- Model – Multivariate regression (or risk‑score) linking entities-pnt001 expression to neurofibrillary‑tangle load
Related Entities
Metadata
| _origin | {'url': None, 'type': 'internal', 'tracked_at': '2026-04-27T08:43:13.416105'} |
| methods | Step 1: Extract expression values of entities-pnt001 from each dataset and map them to brain region and Braak stage. Step 2: Perform differential expression analysis (t‑test/Wilcoxon) between NFT‑high |
| datasets | ['Allen Institute for Brain Science Human Brain Atlas (AHBA) – regional transcriptomic data across prefrontal cortex and hippocampus', 'Mayo Clinic Brain Bank RNA-seq dataset (MayoRNAseq) – temporal c |
| edge_ids | ['0cb41e0c-a626-4012-a6e3-9677cf4dedde'] |
| edge_count | 1 |
| cluster_key | entities-pnt001 ||| neurofibrillary-tangles |
| cluster_type | pair |
| edge_signature | ["0cb41e0c-a626-4012-a6e3-9677cf4dedde"] |
| expected_outputs | ['Figure 1 – Bar plot of entities-pnt001 expression across NFT severity stages with significance bars', 'Figure 2 – Scatter plot with regression line of entities-pnt001 expression vs AT8 density, incl |
| source_relations | ['involved_in'] |
| analysis_question | Can we validate the involvement of entities-pnt001 in neurofibrillary-tangles using human postmortem brain transcriptomic and proteomic datasets? |
📊 Evidence Profile
Evidence Balance
+0%
Certainty
0%
Debates
0
Incoming
0
Outgoing
0
0 supporting
0 contradicting
0 neutral