Evidence map›Paper›PMID 37391799›Full record

ArticleArthritis research & therapy2023

Deconvolution of whole blood transcriptomics identifies changes in immune cell composition in patients with systemic lupus erythematosus (SLE) treated with mycophenolate mofetil.

Mumina Akthar, Nisha Nair, Lucy M Carter, Edward M Vital, Emily Sutton, Neil McHugh, British Isles Lupus Assessment Group Biologics Register (BILAG BR) Consortium, MASTERPLANS Consortium, Ian N Bruce, John A Reynolds

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Arthritis research & therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

10 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 9 institutions in 1 country.

Mumina AktharRheumatology Department, Sandwell and West Birmingham NHS Trust, Birmingham, UK.
Nisha NairCentre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.
Lucy M CarterLeeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, UK.
Edward M VitalLeeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, UK.
Emily SuttonCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal & Dermatological Sciences, The University of Manchester, Manchester, UK.
Neil McHughDepartment of Pharmacy and Pharmacology, University of Bath, Bath, UK.
British Isles Lupus Assessment Group Biologics Register (BILAG BR) Consortium
MASTERPLANS Consortium
Ian N BruceCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal & Dermatological Sciences, The University of Manchester, Manchester, UK.
John A ReynoldsRheumatology Department, Sandwell and West Birmingham NHS Trust, Birmingham, UK. j.a.reynolds.1@bham.ac.uk.
Leeds Teaching Hospitals NHS Trust · GBManchester Academic Health Science Centre · GBNIHR Leeds Musculoskeletal Biomedical Research Unit · GBNIHR Manchester Biomedical Research Centre · GBSandwell & West Birmingham Hospitals NHS Trust · GBUniversity of Bath · GBUniversity of Birmingham · GBUniversity of Manchester · GBVersus Arthritis · GB

Funding

Department of HealthMedical Research Council MR/M01665X/1
6 · The paper itself

Abstract

backgroundSystemic lupus erythematosus (SLE) is a clinically and biologically heterogeneous autoimmune disease. We explored whether the deconvolution of whole blood transcriptomic data could identify differences in predicted immune cell frequency between active SLE patients, and whether these differences are associated with clinical features and/or medication use.

methodsPatients with active SLE (BILAG-2004 Index) enrolled in the BILAG-Biologics Registry (BILAG-BR), prior to change in therapy, were studied as part of the MASTERPLANS Stratified Medicine consortium. Whole blood RNA-sequencing (RNA-seq) was conducted at enrolment into the registry. Data were deconvoluted using CIBERSORTx. Predicted immune cell frequencies were compared between active and inactive disease in the nine BILAG-2004 domains and according to immunosuppressant use (current and past).

resultsPredicted cell frequency varied between 109 patients. Patients currently, or previously, exposed to mycophenolate mofetil (MMF) had fewer inactivated macrophages (0.435% vs 1.391%, p = 0.001), naïve CD4 T cells (0.961% vs 2.251%, p = 0.002), and regulatory T cells (1.858% vs 3.574%, p = 0.007), as well as a higher proportion of memory activated CD4 T cells (1.826% vs 1.113%, p = 0.015), compared to patients never exposed to MMF. These differences remained statistically significant after adjusting for age, gender, ethnicity, disease duration, renal disease, and corticosteroid use. There were 2607 differentially expressed genes (DEGs) in patients exposed to MMF with over-representation of pathways relating to eosinophil function and erythrocyte development and function. Within CD4 + T cells, there were fewer predicted DEGs related to MMF exposure. No significant differences were observed for the other conventional immunosuppressants nor between patients according disease activity in any of the nine organ domains.

conclusionMMF has a significant and persisting effect on the whole blood transcriptomic signature in patients with SLE. This highlights the need to adequately adjust for background medication use in future studies using whole blood transcriptomics.

Indexed as

Autoimmune DiseasesLupus Erythematosus, SystemicGene Expression ProfilingHumansImmunosuppressive AgentsMycophenolic AcidTranscriptomeImmunosuppressive AgentsMycophenolic AcidDeconvolutionMycophenolate mofetilSystemic lupus erythematosusTranscriptomics

Identifiers

PMID37391799
PMCPMC10311871
OpenAlexW4382777245

What OpenQuestion holds

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LicenceCC BY
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.