GEO series

CD4⁺ T Cell Dysregulation in Long COVID: Insights from an Unvaccinated Cohort

GSE334857 Homo sapiens (human) Single-cell RNA-seq 25 samples Submitted 2026/06/23 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 25 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 25 samples: 25 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.

Summary (written by the submitters)

Objective: The pathogenesis of Long COVID (LC) remains poorly understood, with the analysis of immune responses often obscured by variables such as vaccination and reinfection. This study aimed to determine the primary immunological footprint of LC by examining a specific cohort that minimizes these confounding factors. Methods: We analyzed a Brazilian cohort of patients recruited between September 2020 and February 2021, during the first wave of the pandemic (Wuhan-Hu-1 variant), comprising mostly unvaccinated individuals.

Read the full summary ↓

We assessed humoral responses to SARS-CoV-2 and latent viruses in 104 patients. Additionally, we investigated the immune signatures of CD4+ T cells in a subset of 6 LC and 4 recovered control (RC) unvaccinated patients, recruited 1 to 2 months after symptom onset, utilizing a combination of flow cytometry and single-cell RNA sequencing. Results: Systemic humoral responses to SARS-CoV-2 and reactivated latent viruses were comparable between the LC and RC groups, as were the overall distributions of CD4+ T cell subsets. However, single-cell RNA sequencing revealed distinct immune signatures. Antigen-responsive CD4+ T cells in LC patients demonstrated a signature of acute activation, characterized by the upregulation of genes such as CD38 and interferon-stimulated genes, including IFITM1. Furthermore, gene set enrichment analysis indicated that LC patients exhibit increased expression of interferon-alpha/gamma signatures compared to RC. Analysis of the T cell receptor repertoire presented no evidence of clonal expansion. Discussion: Our findings imply that LC immunopathology is driven by a qualitative T cell dysfunction characterized by CD4+ non-proliferative activation more than one month after symptom onset. This pattern is consistent with persistent antigen stimuli, though the underlying mechanism and its therapeutic implications require further investigation

This dataset

Open GSE334857 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 GSE334857_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1476626 and SRA study SRP708096. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

25 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 25 sample titles: 25 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

GSM9798604 Sorted T CD4 memory cells, LC11900, Recovered control
GSM9798605 Sorted T CD4 memory cells, LC11373, Recovered control
GSM9798606 Sorted T CD4 memory cells, LC11703, Recovered control
GSM9798607 Sorted T CD4 memory cells, LC11720, Long COVID
GSM9798608 Sorted T CD4 memory cells, LC11780, Long COVID
GSM9798609 Sorted T CD4 memory cells, LC11837, Recovered control
GSM9798610 Sorted T CD4 naive cells, LC11900, Recovered control
GSM9798611 Sorted T CD4 naive cells, LC11373, Recovered control
GSM9798612 Sorted T CD4 naive cells, LC11703, Recovered control
GSM9798613 Sorted T CD4 naive cells, LC11720, Long COVID
GSM9798614 Sorted T CD4 naive cells, LC11780, Long COVID
GSM9798615 Sorted T CD4 naive cells, LC11837, Recovered control
GSM9798616 Sorted T CD4 naive cells, LC11638, Long COVID
GSM9798617 Sorted T CD4 naive cells, LC11710, Long COVID
GSM9798618 Sorted T CD4 naive cells, LC11713, Long COVID
GSM9798619 Sorted T CD4 naive cells, LC11757, Long COVID
GSM9798620 Sorted T CD4 AIM+ cells, LC11900, Recovered control
GSM9798621 Sorted T CD4 AIM+ cells, LC11373, Recovered control
GSM9798622 Sorted T CD4 AIM+ cells, LC11703, Recovered control
GSM9798623 Sorted T CD4 AIM+ cells, LC11720, Long COVID
GSM9798624 Sorted T CD4 AIM+ cells, LC11780, Long COVID
GSM9798625 Sorted T CD4 AIM+ cells, LC11837, Recovered control
GSM9798626 Sorted T CD4 AIM+ cells, LC11638, Long COVID
GSM9798627 Sorted T CD4 AIM+ cells, LC11713, Long COVID
GSM9798628 Sorted T CD4 AIM+ cells, LC11757, Long COVID

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