Evidence map›Paper›PMID 35906002›Full record

ArticleAnnals of the rheumatic diseases2022

Cross-species transcriptome analysis for early detection and specific therapeutic targeting of human lupus nephritis.

Eleni Frangou, Panagiotis Garantziotis, Maria Grigoriou, Aggelos Banos, Dionysis Nikolopoulos, Antigone Pieta, Stavros A Doumas, Antonis Fanouriakis, Aikaterini Hatzioannou, Theodora Manolakou and 7 more

Open access · hybridAbstract read
In one paragraph

Article in Annals of the rheumatic diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.6field-weighted citation impact, top 6% of its field
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

18 citing papers in PubMed, 23 citations in OpenAlex.

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  10. Molecular Signatures as Guide to Kidney Prognosis in ANCA-Associated Vasculitis.Journal of the American Society of Nephrology : JASN · 2026
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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

17 authors at 5 institutions in 4 countries.

Eleni FrangouLaboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.ORCID http://orcid.org/0000-0003-2516-002X
Panagiotis GarantziotisLaboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Maria Grigoriou *Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Aggelos Banos *Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Dionysis Nikolopoulos *Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.ORCID http://orcid.org/0000-0002-9894-6966
Antigone Pieta *Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Stavros A Doumas *Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Antonis FanouriakisLaboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.ORCID http://orcid.org/0000-0003-2696-031X
Aikaterini Hatzioannou *Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Theodora Manolakou *Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Themis Alissafi *Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Panayotis VerginisLaboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Emmanouil AthanasiadisLaboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Emmanouil DermitzakisDepartment of Genetic Medicine and Development and Institute of Genetics and Genomics of Geneva (iG3), University of Geneva Medical School, Geneve, Switzerland.
George Bertsias *Laboratory of Rheumatology, Autoimmunity and Inflammation, University of Crete Medical School, Heraklion, Greece.
Anastasia Filia *Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Dimitrios T Boumpas *Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece boumpasd@uoc.gr.ORCID http://orcid.org/0000-0002-9812-4671
Biomedical Research Foundation of the Academy of Athens · GRMedizinische Hochschule Hannover · DENational and Kapodistrian University of Athens · GRUniversity of Crete · GRUniversity of Geneva · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPatients with lupus nephritis (LN) are in urgent need for early diagnosis and therapeutic interventions targeting aberrant molecular pathways enriched in affected kidneys.

methodsWe used mRNA-sequencing in effector (spleen) and target (kidneys, brain) tissues from lupus and control mice at sequential time points, and in the blood from 367 individuals (261 systemic lupus erythematosus (SLE) patients and 106 healthy individuals). Comparative cross-tissue and cross-species analyses were performed. The human dataset was split into training and validation sets and machine learning was applied to build LN predictive models.

resultsIn murine SLE, we defined a kidney-specific molecular signature, as well as a molecular signature that underlies transition from preclinical to overt disease and encompasses pathways linked to metabolism, innate immune system and neutrophil degranulation. The murine kidney transcriptome partially mirrors the blood transcriptome of patients with LN with 11 key transcription factors regulating the cross-species active LN molecular signature. Integrated protein-to-protein interaction and drug prediction analyses identified the kinases TRRAP, AKT2, CDK16 and SCYL1 as putative targets of these factors and capable of reversing the LN signature. Using murine kidney-specific genes as disease predictors and machine-learning training of the human RNA-sequencing dataset, we developed and validated a peripheral blood-based algorithm that discriminates LN patients from normal individuals (based on 18 genes) and non-LN SLE patients (based on 20 genes) with excellent sensitivity and specificity (area under the curve range from 0.80 to 0.99).

conclusionsMachine-learning analysis of a large whole blood RNA-sequencing dataset of SLE patients using human orthologs of mouse kidney-specific genes can be used for early, non-invasive diagnosis and therapeutic targeting of LN. The kidney-specific gene predictors may facilitate prevention and early intervention trials.

Indexed as

Lupus Erythematosus, SystemicLupus NephritisAdaptor Proteins, Vesicular TransportAnimalsDNA-Binding ProteinsEarly DiagnosisGene Expression ProfilingHumansMiceRNAAdaptor Proteins, Vesicular TransportDNA-Binding ProteinsRNASCYL1 protein, humanAutoimmune DiseasesAutoimmunityLupus NephritisSystemic Lupus ErythematosusTherapeutics

Identifiers

PMID35906002
PMCPMC9484391
OpenAlexW4288695421

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.