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Genome-wide transcriptome differences associated with perceived discrimination in an urban, community-dwelling middle-aged cohort

GSE244654 Homo sapiens (human) RNA-seq (gene expression) 59 samples Submitted 2025/03/12 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 59 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
59 samples: 8 conditions, mostly with about 8 replicates eachGroups 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
Genome-wide transcriptome differences associated with perceived discrimination in an urban, community-dwelling middle-aged cohortFASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025
Summary (written by the submitters)
Discrimination is a type of social adversity defined as unfair treatment and prejudice against individuals due to membership of a specific group. Discrimination has been linked to several age-related outcomes such as cognitive decline, inflammation, and cardiovascular disease. However, the molecular drivers to these observations are poorly understood.
Read the full summary ↓
Social adverse factors have been associated with proinflammatory and interferon gene expression, a phenomenon described as Conserved Transcriptome Response to Adversity. It is not known whether there are additional genes whose transcription is associated with exposure to discrimination among both African American and White adults. In this study, we have examined how perceived discrimination in African American and White adults affects genome-wide transcriptome differences using RNA sequencing. Perceived discrimination was measured based on responses to lifetime discrimination and racial discrimination questionnaires. Differential gene expression and pathway analysis was conducted in a cohort (N=59) stratified by race, sex, and discrimination exposure. We found that there were 28 significantly differentially expressed genes associated with high discrimination exposure in African American adults when compared to White adults with high discrimination exposure. The most significantly upregulated genes among African Americans with high discrimination exposure were related to immune function immunoglobulin lambda variable 2-11 (IGLV2-11), S100 calcium binding protein B (S100B), immunoglobulin kappa variable 3-20 (IGKV3-20), immunoglobulin kappa variable 4-1 (IGKV4-1); the most significantly downregulated genes were associated with immune modulation and cancer, lung cancer associated transcript 1 (LUCAT1), thrombospondin 1 (THBS1), and actin related protein 2/3 complex inhibitor (ARPIN). In addition, the most significantly upregulated Gene Ontology (GO) biological process among African American men with high exposure to discrimination compared to White male adults with high exposure to discrimination was regulation of cytokine biosynthetic processes. Conversely, immune response was the most significantly downregulated GO biological process among African American women with high discrimination exposure compared White women with high discrimination exposure. Understanding the biological pathways through which adverse social factors like discrimination affect gene expression will be critical in advancing knowledge of age-related health disparities.
Published in
Genome-wide transcriptome differences associated with perceived discrimination in an urban, community-dwelling middle-aged cohort
Pacheco NL, Noren Hooten N, Wu SF et al. · FASEB journal : official publication of the Federation of American Societies for Experimental Biology 2025 · PMID 39887814 · doi:10.1096/fj.202402000R
This dataset
Open GSE244654 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 GSE244654_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 PRJNA1023969 and SRA study SRP464531. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39887814) ↗
Study design
8 conditions, mostly with about 8 replicates each
AA_M_Hi ×8 AA_W_Hi ×8 Wh_M_Hi ×8 Wh_W_Hi ×8 Wh_M_Lo ×7 Wh_W_Lo ×7 AA_W_Lo ×7 AA_M_Lo ×6

Supports a between-group comparison across 59 samples.

How we read this: 8 replicated groups read from 59 sample titles; they account for 59 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

+ 19 more — browse all 59 samples with per-sample file links →

Datasets on a similar topic

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