GEO series

Maturing Neutrophils of Lower Density Associate with Thrombocytopenia in Puumala Orthohantavirus-Caused Hemorrhagic Fever with Renal Syndrome - Human samples

GSE270609 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2024/06/27 Platform GPL18573

At a glance

RNA-seq (gene expression) · human · 16 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: 16 samples: 8 × PUUV, LDG, vs 4 × PUUV, PMN, vs 4 × HC, PMN,Groups 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: Maturing neutrophils of lower density associate with thrombocytopenia in Puumala orthohantavirus-caused hemorrhagic fever with renal syndromeFrontiers in immunology · 2024

Summary (written by the submitters)

Puumala orthohantavirus-caused hemorrhagic fever with renal syndrome (PUUV-HFRS) is characterized by significant neutrophil activation. Neutrophils, the most abundant immune cells in circulation, are equipped to respond rapidly to infections and exhibit a notable heterogeneity. This study aims to identify and characterize different neutrophil subsets in the circulation of PUUV-HFRS patients, focusing on low-density granulocytes (LDGs) and normal density polymorphonuclear cells (PMNs).

Read the full summary ↓

The study finds that PMNs show activation of antiviral pathways, while circulating LDGs increase following acute PUUV-HFRS. Additionally, PUUV-associated LDGs, primarily immature, likely reflect increased bone marrow neutrophil production. Notably, the frequency of LDGs and a "left shift" in blood are associated with the extent of thrombocytopenia, a hallmark of severe HFRS, suggesting a role for maturing neutrophils in disease pathogenesis. Unlike COVID-19 associated LDGs, PUUV LDGs did not exhibit significant immunosuppressive ability, indicating inherent biological differences in LDG responses based on the causative virus or infection kinetics. RNA sequencing was performed on neutrophils isolated from four cohorts: healthy control PMNs, PUUV-infected PMNs, PUUV-infected CD16- LDGs, and PUUV-infected CD16+ LDGs. The RNA sequencing and subsequent bioinformatics analysis were conducted by the Biomedicum Functional Genomics Unit at the Helsinki Institute of Life Science and Biocenter Finland at the University of Helsinki.

Published in

Maturing neutrophils of lower density associate with thrombocytopenia in Puumala orthohantavirus-caused hemorrhagic fever with renal syndrome

Cabrera LE, Tietäväinen J, Jokiranta ST et al. · Frontiers in immunology 2024 · PMID 39011044 · doi:10.3389/fimmu.2024.1419787

This dataset

Open GSE270609 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 GSE270609_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 PRJNA1127560 and SRA study SRP515721. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39011044) ↗

Study design

8 × PUUV, LDG, vs 4 × PUUV, PMN, vs 4 × HC, PMN,

Supports a between-group comparison across 16 samples.

How we read this: 3 replicated groups read from 16 sample titles; they account for 16 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

GSM8348246 PUUV, LDG, rep1 PUUV, LDG,
GSM8348247 PUUV, LDG, rep2 PUUV, LDG,
GSM8348248 PUUV, LDG, rep3 PUUV, LDG,
GSM8348249 PUUV, LDG, rep4 PUUV, LDG,
GSM8348250 PUUV, LDG, rep5 PUUV, LDG,
GSM8348251 PUUV, LDG, rep6 PUUV, LDG,
GSM8348252 PUUV, LDG, rep7 PUUV, LDG,
GSM8348253 PUUV, LDG, rep8 PUUV, LDG,
GSM8348254 PUUV, PMN, rep1 PUUV, PMN,
GSM8348255 PUUV, PMN, rep2 PUUV, PMN,
GSM8348256 PUUV, PMN, rep3 PUUV, PMN,
GSM8348257 PUUV, PMN, rep4 PUUV, PMN,
GSM8348258 HC, PMN, rep1 HC, PMN,
GSM8348259 HC, PMN, rep2 HC, PMN,
GSM8348260 HC, PMN, rep3 HC, PMN,
GSM8348261 HC, PMN, rep4 HC, PMN,

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