GEO series

Coexistent alterations of BAFF and B cell phenotypes in complicated CVID course

GSE333202 Homo sapiens (human) Single-cell RNA-seq 36 samples Submitted 2026/05/29 Platform GPL30173

At a glance

Single-cell RNA-seq · human · 36 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: 36 samples: 36 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: Coexistent alterations of BAFF and B-cell phenotypes in complicated CVID courseThe Journal of allergy and clinical immunology · 2026

Summary (written by the submitters)

Background: Common variable immunodeficiency (CVID) is a primary immunodeficiency marked by impaired antibody production and infection susceptibility, with about half developing non-infectious complications. BAFF elevation and genetic variants in a BAFF receptor, transmembrane activator and CAML interactor (TACI), frequently occur in CVID.

Read the full summary ↓

While these findings associate with autoimmune and lymphoproliferative complications, pathogenic mechanisms remain incompletely defined. Objective: This work explored how coexistent changes in BAFF, its receptors, and B cell subsets may shape CVID. Methods: Plasma protein measurement, spectral flow cytometry, and single-cell RNA sequencing was applied. Results: CVID with autoimmune cytopenias and lymphoid hyperplasia had elevated plasma BAFF:TACI ratio and increased transitional and activated naïve B cells. Activated naïve B cells from CVID patients had increased mRNA of genes downstream of BAFF receptor (BAFF-R) that promote B cell survival. Also on these expanded subsets, BAFF-R surface protein decreased, consistent with negative feedback, while autoreactive B cell receptor (BCR) VH4-34 clonality increased. Conclusions: Novel application of spectral flow cytometry, paired BCR sequencing RNA-seq, and measurement of BAFF and related proteins in plasma found CVID with autoimmune and lymphoproliferative complications to be marked by coexistent BAFF and B cell subset dysregulation. This included increased plasma BAFF, BAFF:TACI ratio, and transitional and activated naïve B cells with reduced BAFF-R expression and BCR repertoire diversity. The expanded activated naïve B cell subset in CVID had increased expression of BAFF-R-driven genes that subvert B cell tolerance as well as increased autoreactive VH4-34 clonality. Convergence of BAFF, its receptors, and B cell subset dysregulation, should be further explored in CVID.

Published in

Coexistent alterations of BAFF and B-cell phenotypes in complicated CVID course

Matson EM, Ware MS, Feng F et al. · The Journal of allergy and clinical immunology 2026 · PMID 42219089 · doi:10.1016/j.jaci.2026.04.029

This dataset

Open GSE333202 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 GSE333202_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 PRJNA1470480 and SRA study SRP703605. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42219089) ↗

Study design

36 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 36 sample titles: 36 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

GSM9758914 transitional B cells, subject 1
GSM9758915 naïve B cells, subject 1, GEX
GSM9758916 activated naïve B cells, subject 1, GEX
GSM9758917 transitional B cells, subject 2, GEX
GSM9758918 naïve B cells, subject 2, GEX
GSM9758919 activated naïve B cells, subject 2, GEX
GSM9758920 transitional B cells, subject 3, GEX
GSM9758921 naïve B cells, subject 3, GEX
GSM9758922 activated naïve B cells, subject 3, GEX
GSM9758923 transitional B cells, subject 4, GEX
GSM9758924 naïve B cells, subject 4, GEX
GSM9758925 activated naïve B cells, subject 4, GEX
GSM9758926 transitional B cells, subject 5, GEX
GSM9758927 naïve B cells, subject 5, GEX
GSM9758928 activated naïve B cells, subject 5, GEX
GSM9758929 transitional B cells, subject 6, GEX
GSM9758930 naïve B cells, subject 6, GEX
GSM9758931 activated naïve B cells, subject 6, GEX
GSM9758932 transitional B cells, subject 1,BCR
GSM9758933 naïve B cells, subject 1, BCR
GSM9758934 activated naïve B cells, subject 1, BCR
GSM9758935 transitional B cells, subject 2, BCR
GSM9758936 naïve B cells, subject 2, BCR
GSM9758937 activated naïve B cells, subject 2, BCR
GSM9758938 transitional B cells, subject 3, BCR
GSM9758939 naïve B cells, subject 3, BCR
GSM9758940 activated naïve B cells, subject 3, BCR
GSM9758941 transitional B cells, subject 4, BCR
GSM9758942 naïve B cells, subject 4, BCR
GSM9758943 activated naïve B cells, subject 4, BCR
GSM9758944 transitional B cells, subject 5, BCR
GSM9758945 naïve B cells, subject 5, BCR
GSM9758946 activated naïve B cells, subject 5, BCR
GSM9758947 transitional B cells, subject 6, BCR
GSM9758948 naïve B cells, subject 6, BCR
GSM9758949 activated naïve B cells, subject 6, BCR

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