Foundry120 atlas

Concordant B and T Cell Heterogeneity Inferred from the Multiomic Landscape of Peripheral Blood Mononuclear Cells in a Crohn's Disease Cohort

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Dataset overview

Participants 3
Samples 13
Reuse readiness 4.6/10 evidence-backed score

Concordant B and T Cell Heterogeneity Inferred from the Multiomic Landscape of Peripheral Blood Mononuclear Cells in a Crohn's Disease Cohort.

Abstract

<h4>Background and aims</h4>Crohn's disease is characterized by inflammation in the gastrointestinal tract due to a combination of genetic, immune, and environmental factors. Transcriptomic and epigenomic profiling of intestinal tissue of Crohn's disease patients have revealed valuable insights into pathology, however have not been conducted jointly on less invasive peripheral blood mononuclear cells (PBMCs). Furthermore, the heterogeneous responses to treatments among individuals with Crohn's disease imply hidden diversity of pathological mechanisms.<h4>Methods</h4>We employed single nucleus multiomic analysis, integrating both snRNA-seq and snATAC-seq of PBMCs with a variety of open source bioinformatics applications.<h4>Results</h4>Our findings reveal a diverse range of transcriptional signatures among individuals, highlighting the heterogeneity in PBMC profiles. Nevertheless, striking concordance between three heterogeneous groups was observed across B cells and T cells. Differential gene regulatory mechanisms partially explain these profiles, notably including a signature involving TGFß signaling in two individuals with Crohn's disease. A mutation mapped to a transcription factor binding site within a differentially accessible peak associated with the expression of this pathway, with implications for a personalized approach to understanding disease pathology.<h4>Conclusions</h4>This study highlights how multiomic analysis can reveal common regulatory mechanisms that underlie heterogeneity of PBMC profiles, one of which may be specific to inflammatory disease.

Study facts

Organism
Homo sapiens
Platform
single nucleus multiomic
Age group
—
Disease groups
—
Anatomical sites
PBMC

Data availability

  • Raw counts
  • Processed matrix

File types MTXRDSTSV

Files and samples

Strengths & limitations for reuse

Strengths

  • Raw counts are advertised
  • Processed matrices are advertised
  • Participant counts are documented

Limitations

  • Not documented: cell metadata are advertised
Extraction evidence & provenance

Each extracted field is shown with the source excerpt and location used to resolve it.

Assay

FieldValueEvidence
assay.assay_type single nucleus multiomic
We employed single nucleus multiomic analysis, integrating both snRNA-seq and snATAC-seq of PBMCs with a variety of open source bioinformatics applications.

Section series_summary, offset —

assay.reference_genome hg38
Assembly: hg38

Section sample_values_with_sample_counts.data_processing, offset —

assay.sequencing_type snrna_seq
To investigate the heterogeneity of gene regulation in Crohn's disease and healthy PBMC using multiome snRNA-seq and snATAC-seq.

Section series_overall_design, offset —

Cohort

FieldValueEvidence
cohort.total_participants 3 computed
3 distinct subject/participant IDs across GEO samples

Section GEO family SOFT, offset —

Data_Assets

FieldValueEvidence
data_assets.open_access True
Public on Oct 10 2023

Section series_status, offset —

data_assets.processed_matrix True
GSE244831_crohns_multiome.rds.gz

Section filelist.txt, offset —

data_assets.raw_counts True
"suppfile": "MTX, RDS, TSV"

Section suppfile, offset —

Specimens

FieldValueEvidence
specimens.anatomical_sites ['PBMC']
"source_name": {"PBMC": 26}

Section sample_values_with_sample_counts.source_name, offset —

specimens.number_of_samples 13
"molecule": {"total RNA": 13, "genomic DNA": 13}

Section sample_values_with_sample_counts.molecule, offset —