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Replicative senescence in neural progenitors induces senescence-associated markers in midbrain organoids

GSE331395 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/06/17 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 24 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
24 samples: 8 conditions, mostly in triplicateGroups 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.
Summary (written by the submitters)
Aging is the primary risk factor for Parkinson’s disease (PD), and astrocyte senescence, or astrosenescence, has emerged as a potential mechanism through which aging may progressively impair glial homeostatic neuronal support and render the brain more vulnerable to neurodegeneration. Yet human experimental models that specifically recapitulate astrosenescence within a PD-relevant genetic background are lacking.
Read the full summary ↓
Here, we applied passage-induced replicative exhaustion to human iPSC-derived neuroepithelial stem cells (NESCs) from healthy donors and LRRK2 G2019S PD patients to establish an in vitro midbrain aging model. Extended passaging induced senescence-associated changes in NESCs, including reduced proliferative capacity, apoptosis resistance, reduction in telomerase activity, and sustained DNA damage response (DDR) activation, while preserving ventral midbrain identity and differentiation potential. Astrocytes derived from aged progenitors recapitulated multiple senescence hallmarks, including increase in SA-β-gal activity, nuclear lamina disruption, persistent DDR activation, and alteration in mitochondrial homeostasis. In human midbrain organoids (hMOs), passage-induced aging was associated with astrocyte-specific DDR activation, widespread lipidomic remodeling, and a selective reduction of dopaminergic neuron content in LRRK2 G2019S organoids compared to healthy donor-derived organoids. Multi-modal analysis of NESCs, astrocytes, and hMOs further revealed that the LRRK2 G2019S genetic background not only shifts baseline cellular states toward an aged-like profile but actively reshapes aging trajectories in a cell-type- and feature-dependent manner. Together, this work establishes a human iPSC-based midbrain model recapitulating key features of cellular senescence in both healthy and LRRK2 G2019S contexts and provides an in vitro platform to investigate the contribution of astrosenescence to PD-related neurodegeneration.
This dataset
Open GSE331395 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 GSE331395_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1468005 and SRA study SRP701978. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
NESCs, HT cell line, control, ×3 NESCs, HT cell line, aged, ×3 NESCs, PD1 cell line, control, ×3 NESCs, PD1 cell line, aged, ×3 NESCs, PD1 GC cell line, control, ×3 NESCs, PD1 GC cell line, aged, ×3 NESCs, PD2 cell line, control, ×3 NESCs, PD2 cell line, aged, ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 of them. 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
Datasets on a similar topic

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