Evidence map›Paper›PMID 38014022›Full record

ArticlebioRxiv : the preprint server for biology2023

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

Samuel Schäfer, Martin Smelik, Oleg Sysoev, Yelin Zhao, Desiré Eklund, Sandra Lilja, Mika Gustafsson, Holger Heyn, Antonio Julia, István A Kovács and 7 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors at 5 institutions in 3 countries.

Samuel SchäferCentre for Personalised Medicine, Linköping University; Linköping, Sweden.ORCID 0000-0002-3101-9367
Martin SmelikCentre for Personalised Medicine, Linköping University; Linköping, Sweden.
Oleg SysoevDivision of Statistics and Machine Learning, Department of Computer and Information Science, Linkoping University; Linköping, Sweden.
Yelin ZhaoCentre for Personalised Medicine, Linköping University; Linköping, Sweden.
Desiré EklundCentre for Personalised Medicine, Linköping University; Linköping, Sweden.
Sandra LiljaCentre for Personalised Medicine, Linköping University; Linköping, Sweden.
Mika GustafssonDivision for Bioinformatics, Department of Physics, Chemistry and Biology, Linköping University; Linköping, Sweden.
Holger HeynCNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.
Antonio JuliaGrup de Recerca de Reumatologia, Institut de Recerca Vall d'Hebron, Barcelona, España.
István A KovácsDepartment of Physics and Astronomy, Northwestern University, Evanston, IL 60208, USA.
Joseph LoscalzoDivision of Cardiovascular Medicine, Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School; Boston, MA, USA.
Sara MarsalGrup de Recerca de Reumatologia, Institut de Recerca Vall d'Hebron, Barcelona, España.
Huan ZhangCentre for Personalised Medicine, Linköping University; Linköping, Sweden.
Xinxiu LiCentre for Personalised Medicine, Linköping University; Linköping, Sweden.
Danuta GawelCentre for Personalised Medicine, Linköping University; Linköping, Sweden.
Hui WangNorthwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208, USA.
Mikael BensonCentre for Personalised Medicine, Linköping University; Linköping, Sweden.
Linköping University · SENorthwestern University · USVall d'Hebron Institut de Recerca · ESBrigham and Women's Hospital · USUniversitat Pompeu Fabra · ES

Funding

L-2-Hydroxyglutarate and Metabolic Remodeling in HypoxiaR01HL155107 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI Joseph Loscalzo · 2021 to 2026
$4.1M
Personalized protein-protein interactomes and precision medicine in pulmonary arterial hypertensionR01HL155096 · NHLBI · UNIVERSITY OF MARYLAND BALTIMORE · PI MARON, BRADLEY · 2021 to 2024
$1.6M
NHLBI NIH HHS R01 HL155096NHLBI NIH HHS R01 HL155107
6 · The paper itself

Abstract

Background: 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. Methods: 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. Results: scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive Conclusion: 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).

Indexed as

digital twindrug predictiondrug prioritisationdrug repurposingimmune-mediated inflammatory diseasescRNA-seqsingle-cell RNA sequencing

Identifiers

PMID38014022
PMCPMC10680570
OpenAlexW4388651357

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.