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CNS-penetrant NLRP3 inhibitor TN-783 achieves durable weight loss and reverses hypothalamic inflammation in diet-induced obesity

GSE308884 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/07/21 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 18 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
Mus musculus (mouse)
Samples
18 samples: 6 × DIO+ Vehicle vs 6 × DIO+ TN-783 vs 6 × Lean ControlGroups 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)
The NLRP3 inflammasome is a key mediator of innate immunity that integrates inflammatory and metabolic stress signals. Increased chronic activation of this critical pathway has been implicated in obesity, with increased hypothalamic neuroinflammation linked to dysregulation of energy balance. TN-783 is an investigational CNS-penetrant small-molecule NLRP3 inhibitor that potently suppresses inflammasome activation.
Read the full summary ↓
In diet-induced obese (DIO) mice, TN-783 produced progressive and sustained weight loss. Transcriptomic profiling revealed partial reversal of obesity-associated molecular changes, particularly among genes involved in inflammation and neuronal signaling.
This dataset
Open GSE308884 in finder → Find more mouse 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 GSE308884_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 PRJNA1333326 and SRA study SRP625478. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 × DIO+ Vehicle vs 6 × DIO+ TN-783 vs 6 × Lean Control

Supports a between-group comparison across 18 samples.

How we read this: 3 replicated groups read from 18 sample titles; they account for 18 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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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.