GEO series

Haploinsufficiency in PTPN2 leads to early onset systemic autoimmunity from Evans syndrome to lupus

GSE270302 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2024/06/21 Platform GPL24676

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: 24 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: Haploinsufficiency in PTPN2 leads to early-onset systemic autoimmunity from Evans syndrome to lupusThe Journal of experimental medicine · 2024

Summary (written by the submitters)

An exome sequencing strategy employed to identify pathogenic variants in patients with pediatric-onset systemic lupus or Evans syndrome resulted in the discovery of six novel monoallelic mutations in PTPN2. PTPN2 is a phosphatase that acts as an essential negative regulator of the JAK/STAT pathways downstream of several cytokine pathways.

Read the full summary ↓

All identified mutations led to a loss of PTPN2 regulatory function as evidenced by in vitro cytokine reporter and phosphatase assays, and by hyperproliferation of patients’ T cells stimulated with cytokines. Furthermore, patients exhibited high serum levels of various inflammatory cytokines, mimicking the profile observed in individuals with gain-of-function mutations in various STAT factors. Flow cytometry analysis of patients’ blood cells revealed typical alterations associated with autoimmunity, such as an expansion of CD11c+ B cells and follicular helper T cells, and all patients presented with anti-platelet or other autoantibodies. These findings further supported the notion that a loss of function in negative regulators of cytokine pathways can lead to a broad spectrum of autoimmune manifestations and that PTPN2 along with SOCS1 haploinsufficiency constitute a new group of monogenic autoimmune diseases that can benefit from targeted therapy.

Published in

Haploinsufficiency in PTPN2 leads to early-onset systemic autoimmunity from Evans syndrome to lupus

Jeanpierre M, Cognard J, Tusseau M et al. · The Journal of experimental medicine 2024 · PMID 39028869 · doi:10.1084/jem.20232337

This dataset

Open GSE270302 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 GSE270302_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 PRJNA1126155 and SRA study SRP514986. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39028869) ↗

Study design

24 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 24 sample titles: 24 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

GSM8339279 A1, IFNa
GSM8339280 A1, IL2
GSM8339281 A1, NS
GSM8339282 A2, IFNa
GSM8339283 A2, IL2
GSM8339284 A2, NS
GSM8339285 B1, IFNa
GSM8339286 B1, IL2
GSM8339287 B1, NS
GSM8339288 C1, IFNa
GSM8339289 C1, IL2
GSM8339290 C1, NS
GSM8339291 D1, IFNa
GSM8339292 D1, IL2
GSM8339293 D1, NS
GSM8339294 HC1, IFNa
GSM8339295 HC1, IL2
GSM8339296 HC1, NS
GSM8339297 HC2, IFNa
GSM8339298 HC2, IL2
GSM8339299 HC2, NS
GSM8339300 HC3, IFNa
GSM8339301 HC3, IL2
GSM8339302 HC3, NS

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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.