Evidence map›Paper›PMID 41841101›Full record

ArticleBioinformatics advances2026

SLE-diseaseome: a comprehensive meta-collection of systemic lupus erythematosus relevant functional pathways.

Daniel Toro-Domínguez, Chang Wang, Iván Ellson-Lancho, Jordi Martorell-Marugán, Pedro Carmona-Sáez, Marta E Alarcón-Riquelme, Frédéric Baribaud

Abstract read
In one paragraph

Article in Bioinformatics advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Daniel Toro-DomínguezUnit of Inflammatory Diseases, Department of Environmental Medicine, Karolinska Institute, Solna, 171 77, Sweden.ORCID https://orcid.org/0000-0001-8440-312X
Chang WangICV Translational Early Development, Bristol Myers Squibb, Lawrence, NJ 08543, United States.
Iván Ellson-LanchoGENYO, Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Granada 18016, Spain.
Jordi Martorell-MarugánGENYO, Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Granada 18016, Spain.ORCID https://orcid.org/0000-0002-5186-0735
Pedro Carmona-SáezGENYO, Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Granada 18016, Spain.
Marta E Alarcón-RiquelmeUnit of Inflammatory Diseases, Department of Environmental Medicine, Karolinska Institute, Solna, 171 77, Sweden.
Frédéric BaribaudICV Translational Early Development, Bristol Myers Squibb, Lawrence, NJ 08543, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: Systemic lupus erythematosus patients exhibit a broad clinical spectrum of manifestations and suffer from high rates of treatment failure. These can be attributed to disease heterogeneity due to differentially dysregulated pathways. Precision medicine considering the individualized molecular disease driving mechanisms is a promising strategy to address challenges imposed by disease heterogeneity. Available patient blood transcriptome data coupled with pathway-based single-sample scoring approaches have been extensively employed to reveal molecular footprints of disease states and progression as well as delineate population heterogeneity. However, systemic understanding of pathways involved in disease pathogenesis remains lacking. Results: We created a SLE-diseaseome, an integrative multi-cohort collection of disease-relevant functional gene sets. This resource contains a comprehensive collection of disease-specific gene signatures combining knowledge from several pathway databases and signature sources robustly defined by integrating multiple studies. It offers reliable and extensive reference signatures in a disease-specific manner for functional interpretation of molecular data from clinical studies. Availability and implementation: The code used to run the pipeline and the R object containing the SLE-diseaseome collection are available at https://github.com/dtordom/SLEDiseaseome.

Identifiers

PMID41841101
PMCPMC12989159

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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.