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Molecular Signatures of Resilience to Alzheimer’s Disease in Neocortical Layer 4 Neurons

GSE263468 Homo sapiens (human) Single-nucleus RNA-seq 244 samples Submitted 2025/08/24 Platform GPL24676Platform GPL18573
At a glance

Single-nucleus RNA-seq · human · 244 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
244 samples: 244 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Molecular signatures of resilience to Alzheimer's disease in neocortical layer 4 neuronsNature communications · 2026
Summary (written by the submitters)
Single-cell omics is advancing our understanding of selective neuronal vulnerability in Alzheimer’s disease (AD), revealing specific subtypes that are either susceptible or resilient to neurodegeneration. Using single-nucleus and spatial transcriptomics to compare neocortical regions affected early (prefrontal cortex and precuneus) or late (primary visual cortex) in AD, we identified a resilient excitatory population in layer 4 of the primary visual cortex expressing RORB, CUX2, and EYA4.
Read the full summary ↓
Layer 4 neurons in association neocortex shared overlapping molecular signatures of resilience. Early in the disease, resilient neurons upregulated genes associated with synapse maintenance, synaptic plasticity, calcium homeostasis, and neuroprotective factors, including GRIN2A, RORA, NRXN1, NLGN1, NCAM2, FGF14, NRG3, NEGR1, and CSMD1. We also identified KCNIP4, which encodes a voltage-gated potassium (Kv) channel-interacting protein that interacts with Kv4.2 channels and presenilins, as a key factor linked to resilience. KCNIP4 was consistently upregulated in the early stages of pathology. Furthermore, AAV-mediated overexpression of Kcnip4 in a humanized AD mouse model reduced the expression of the activity-dependent genes Arc and c-Fos, suggesting compensatory mechanisms against neuronal hyperexcitability. Our dataset provides a valuable resource for investigating mechanisms underlying resilience to neurodegeneration.
Published in
Molecular signatures of resilience to Alzheimer's disease in neocortical layer 4 neurons
Dharshini SAP, Sanz-Ros J, Pan J et al. · Nature communications 2026 · PMID 41620473 · doi:10.1038/s41467-026-68920-4
This dataset
Open GSE263468 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE263468_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1097599 and SRA study SRP500433. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41620473) ↗
Study design
244 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 244 sample titles: 244 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 204 more — browse all 244 samples with per-sample file links →

Datasets on a similar topic

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