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Cutaneous adipose tissue has a strong inflammatory signature in psoriasis patients, and it is partly IL-17 dependent.

GSE287022 Homo sapiens (human) RNA-seq (gene expression) 241 samples Submitted 2026/01/14 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 241 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
241 samples: 241 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
Cutaneous adipose tissue carries a strong inflammatory signature in patients with psoriasisJCI insight · 2026
Summary (written by the submitters)
Background: Psoriasis is an inflammatory skin disease associated with systemic inflammation and comorbidities such as diabetes and cardiovascular disease. Although the association between psoriasis and obesity has been studied extensively, the role of cutaneous adipose tissue (CAT) in pathogenesis of psoriasis remains unclear. Objectives This study aimed to provide a comprehensive evaluation of the CAT transcriptome in psoriasis patients and investigate the effects of IL-17 pathway blockade on adipose tissue inflammation.
Read the full summary ↓
Methods: In this randomized, double-blind, placebo-controlled phase 4 study (ObePso study), CAT biopsies were obtained from lesional (LS-CAT) and non-lesional skin (NL-CAT) of 82 psoriasis patients and 15 healthy controls. Patients were randomized to receive either secukinumab or placebo for 12 weeks. RNA sequencing and subsequent analyses were performed to identify differentially expressed genes and pathways. Results: Psoriatic CAT showed significant gene expression differences compared to controls, with 2132 differentially expressed transcripts identified. Both LS-CAT and NL-CAT exhibited activation of IL-17-induced, antimicrobial peptides-related, and neutrophil degranulation-related pathways. Obesity expanded differential gene expression in psoriasis by more than 100%, suggesting an additive or synergistic interaction between psoriasis and adiposity. Obese psoriasis patients showed activation of pathways related to collagen metabolism, cytokine storm signaling, and IL-17A signaling. Secukinumab treatment significantly improved inflammation in psoriatic CAT, with obese patients showing greater improvement than non-obese patients. Conclusions: This study provides the first comprehensive evaluation of the adipose tissue transcriptome in psoriasis patients. The findings reveal a strong inflammatory signature in psoriatic CAT, which is partly IL-17 dependent. The study also demonstrates that obesity amplifies the inflammatory response in psoriatic adipose tissue. IL-17 blockade with secukinumab significantly improved CAT inflammation, with enhanced benefits observed in obese individuals. These results highlight the potential role of adipose tissue in psoriasis pathogenesis and suggest that targeting adipose tissue inflammation may be a valuable therapeutic approach, particularly in obese psoriasis patients.
Published in
Cutaneous adipose tissue carries a strong inflammatory signature in patients with psoriasis
Shishido-Takahashi N, Garcet S, Cueto I et al. · JCI insight 2026 · PMID 41774505 · doi:10.1172/jci.insight.194171
This dataset
Open GSE287022 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 GSE287022_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 PRJNA1210993 and SRA study SRP557480. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41774505) ↗
Study design
241 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 241 sample titles: 241 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

+ 201 more — browse all 241 samples with per-sample file links →

Datasets on a similar topic

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