Foundry120 atlas

← IBD single-cell transcriptomics

Network analyses of single cell-based digital twins for individualized treatment of antigen induced arthritis in mice.

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Dataset overview

Participants 9
Samples 9
Reuse readiness 7.0/10 evidence-backed score

scDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases.

Schäfer S, Smelik M, Sysoev O, Zhao Y, Eklund D, Lilja S, Gustafsson M, Heyn H, et al. · Genome medicine · 2024

Abstract

<h4>Background</h4>Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs.<h4>Methods</h4>Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs.<h4>Results</h4>scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment.<h4>Conclusions</h4>We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio ).

doi:10.1186/s13073-024-01314-7 ↗ PMID 38509600 ↗ PMC10956347 ↗

Study facts

Organism
Mus musculus
Platform
NextSeq 500/550
Age group
paediatric
Disease groups
—
Anatomical sites
joint

Data availability

  • Raw counts
  • Processed matrix
  • Analysis code

File types CSV

Strengths & limitations for reuse

Strengths

  • Raw counts are advertised
  • Processed matrices are advertised
  • Cell metadata are advertised
  • Analysis code is available
  • Participant mapping is available
  • Participant counts are documented
Extraction evidence & provenance

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

Assay

FieldValueEvidence
assay.assay_type Seq-Well
scRNA sequencing was performed using the Seq-Well technique

Section Antigen-induced arthritis mouse model, offset —
assay.platform NextSeq 500/550
each library was sequenced once, except for one library, which was sequenced twice using the NextSeq 500/550 system.

Section Antigen-induced arthritis mouse model, offset —
assay.reference_genome GRCm38
The indexed reference for alignment of reads was generated from GRCm38 (June 2017, Ensembl) using STAR software (2.5.3).

Section Antigen-induced arthritis mouse model, offset —
assay.sequencing_type scrna_seq
scRNA sequencing was performed using the Seq-Well technique

Section Antigen-induced arthritis mouse model, offset —

Cohort

FieldValueEvidence
cohort.age_group paediatric from source
GEO age characteristics: 8 weeks old; 8 weeks old; 8 weeks old; 8 weeks old; 8 weeks old; 8 weeks old; 8 weeks old; 8 weeks old; 8 weeks old

Section GEO family SOFT, offset —
cohort.disease_activity_metadata_available True
specimens were examined in a blinded manner for pannus formation, cartilage and subchondral bone destruction, and synovial hypertrophy on an arbitrary scale, 0–3

Section Antigen-induced arthritis mouse model, offset —
cohort.total_participants 9
scRNA-seq data were generated from whole joints of five inbred AIA mice and four naïve mice.

Section Results — scDrugPrio development and evaluation in antigen-induced arthritis, offset —

Data_Assets

FieldValueEvidence
data_assets.analysis_code True
The codes associated with scDrugPrio analysis are available from GitHub

Section Availability of data and materials, offset —
data_assets.cell_metadata True
Additional file 3: AIA data. Includes quality cut-offs, cell type markers, DEGs, metadata for scDrugPrio application to the AIA data set

Section Supplementary Information, offset —
data_assets.open_access True
"series_status": "Public on Jul 31 2023"

Section series metadata, offset —
data_assets.participant_metadata True
"age": {"8 weeks old": 9}, "sex": {"female": 9}, "strain": {"129/Sve": 9}, "tissue": {"Joint": 9}, "disease": {"Sick": 5, "Healthy": 4}

Section sample characteristics, offset —
data_assets.processed_matrix True
GSE193536_Joint_expression_matrix.csv.gz

Section dataset-authority, offset —
data_assets.raw_counts True
Matrix table with transcript counts of each gene (rows) within each cell (columns).

Section data_processing, offset —

Processing

FieldValueEvidence
processing.cell_type_annotation_method Marker gene coexpression
Cell types were assigned to each cluster based on the relative coexpression of several known cell type marker genes

Section Cell typing, offset —
processing.quality_control_reported True
Quality control, where cells with less than 10,000 reads, 400 transcripts, or 200 genes, or more than 20% mitochondrial genes were sorted out.

Section data_processing, offset —

Specimens

FieldValueEvidence
specimens.anatomical_sites ['joint']
the whole left joint was prepared for scRNA-seq.

Section series_overall_design, offset —
specimens.inflamed_status_available True
"disease": {"Sick": 5, "Healthy": 4}

Section sample characteristics, offset —
specimens.number_of_cells 16751
Quality cut-offs resulted in a total of 16,751 cells

Section Antigen-induced arthritis, offset —
specimens.number_of_samples 9
"sample_count": 9

Section series metadata, offset —
specimens.participant_to_sample_mapping_available True
"samples": [{"title": "Healthy mouse 2", "accession": "GSM5813912"}

Section samples, offset —