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Sex differences and immune correlates of Long COVID development, persistence, and resolution

GSE270479 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2024/11/13 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 15 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
15 samples: 15 × Long COVID cohort, sublibraryGroups 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
Sex differences and immune correlates of Long Covid development, symptom persistence, and resolutionScience translational medicine · 2024
Summary (written by the submitters)
Sex differences have been observed in acute coronavirus disease 2019 (COVID-19) and Long Covid (LC) outcomes, with greater disease severity and mortality during acute infection in males and greater proportions of females developing LC. We hypothesized that sex-specific immune dysregulation contributes to LC pathogenesis.
Read the full summary ↓
To investigate the immunologic underpinnings of LC development and symptom persistence, we performed multi-omic analyses on blood samples obtained during acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and 3 and 12 months post infection in a cohort of 45 patients who either developed LC or recovered. Several sex-specific immune pathways were associated with LC. Males who would later develop LC exhibited increases in transforming growth factor (TGF)-β signaling during acute infection, whereas females who would go on to develop LC had reduced TGFB1 expression. Females who developed LC demonstrated increased expression of XIST, an RNA gene implicated in autoimmunity, during acute infection compared with females who recovered. Many immune features of LC were also conserved across sexes, such as alterations in monocyte phenotype and activation state. Nuclear factor (NF)-κB transcription factors were up-regulated in many cell types at acute and convalescent time points. Those with ongoing LC demonstrated reduced ETS1 expression across lymphocyte subsets and elevated intracellular IL-4 in T cell subsets, suggesting that ETS1 alterations may drive aberrantly elevated Th2-like responses in LC. Altogether, this study describes multiple innate and adaptive immune correlates of LC, some of which differ by sex, and offers insights toward the pursuit of tailored therapeutics.
Published in
Sex differences and immune correlates of Long Covid development, symptom persistence, and resolution
Hamlin RE, Pienkos SM, Chan L et al. · Science translational medicine 2024 · PMID 39536117 · doi:10.1126/scitranslmed.adr1032
This dataset
Open GSE270479 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 GSE270479_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 PRJNA1124166 and SRA study SRP514070. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39536117) ↗
Study design
15 × Long COVID cohort, sublibrary

Supports a between-group comparison across 15 samples.

How we read this: 1 replicated groups read from 15 sample titles; they account for 15 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
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