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analysis proposal

Analysis Proposal: entities-pnt001 ||| neurofibrillary-tangles

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
Related Entities
entities-pnt001neurofibrillary-tangles
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