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Defining the Inflammation and Immunity Transcriptome in Severe Malarial Anemia for Immunotherapeutic Discovery

GSE255403 Homo sapiens (human) RNA-seq (gene expression) 66 samples Submitted 2024/04/16 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 66 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
66 samples: 41 × nonSMA vs 25 × SMAGroups 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
Entire expressed peripheral blood transcriptome in pediatric severe malarial anemiaNature communications · 2024
Summary (written by the submitters)
Malaria continues to pose a significant public health threat, with millions of cases and hundreds of thousands of deaths reported annually, primarily in sub-Saharan Africa. The disease disproportionally affects children under five years of age residing in holoendemic Plasmodium falciparum transmission regions, who account for 94% of the cases and 80% of the mortality.
Read the full summary ↓
Young children are highly vulnerable to developing life-threatening severe malarial anemia [SMA, hemoglobin (Hb)<5.0 g/dL]. The overall goal of the project was to identify critical gene pathways within the transcriptome that mediate disease severity and then target these specific genes with compounds that elicit expression profiles witnessed in children with milder forms of disease. To achieve this goal, we are investing the following specific aims: 1) Determine how changing temporal dynamics of gene pathways in the Malarial Immunity Transcriptome promote SMA during acute disease; 2) Determine how changes in gene pathways in the Malarial Immunity Transcriptome mediate malarial severity throughout the development of naturally acquired immunity; and 3) Identify immunotherapeutic targets in the Malarial Immunity Transcriptome that can be used to reduce malaria disease severity and improve clinical outcomes in future trials. To successfully complete these aims, we are determining how host profiles impact on acute disease over 14 days. We will utilize Ex vivo samples from the cohort to test the effect of immunotherapeutic compounds on host expression profiles. Accomplishing these goals will have broad reaching translational implications for: (1) identifying at-risk groups, and (2) prioritizing compounds that can be used to improve clinical outcomes in future immunotherapy trials.
Published in
Entire expressed peripheral blood transcriptome in pediatric severe malarial anemia
Anyona SB, Cheng Q, Wasena SA et al. · Nature communications 2024 · PMID 38866743 · doi:10.1038/s41467-024-48259-4
This dataset
Open GSE255403 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 GSE255403_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 PRJNA1074811 and SRA study SRP502361. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38866743) ↗
Study design
41 × nonSMA vs 25 × SMA

Supports a between-group comparison across 66 samples.

How we read this: 2 replicated groups read from 66 sample titles; they account for 66 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

+ 26 more — browse all 66 samples with per-sample file links →

Datasets on a similar topic

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